Internship Openings

62 Intern positions are currently open.

Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERL's employees to perform their job duties may result in discipline up to and including discharge.

Qualified applicants for MERL internships are individuals who have or can obtain full authorization to work in the U.S. and do not require export licenses to receive information about the projects they will be exposed to at MERL. The U.S. government prohibits the release of information without an export license to citizens of several countries, including, without limitation, Cuba, Iran, North Korea, Sudan and Syria (Country Groups E:1 and E:2 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).


  • SA1132: End-to-end acoustic analysis recognition and inference

    • MERL is looking for an intern to work on fundamental research in the area of end-to-end acoustic analysis, recognition, and inference using machine learning techniques such as deep learning. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for high impact publication. The ideal candidate would be a senior Ph.D. student with experience in one or more of source separation, speech recognition, and natural language processing including practical machine learning algorithms with related programming skills. The duration of the internship is expected to be 3-6 months.

    • Research Areas: Speech & Audio
    • Host: Takaaki Hori
    • Apply Now
  • SA1245: Source Separation

    • We are seeking graduate students interested in helping advance the field of source separation and speech enhancement in extreme environments using the latest developments in deep learning. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for publication. The ideal candidate would be a senior Ph.D. student with experience in audio signal processing, speech modeling, probabilistic modeling, and deep learning. The duration of the internship is expected to be 3-6 months.

    • Research Areas: Speech & Audio
    • Host: Gordon Wichern
    • Apply Now
  • SA1246: Audio Visual Semantic Understanding

    • MERL is looking for an intern to work on fundamental research in the area of audiovisual semantic understanding for scene-aware dialog technologies by combining end-to-end dialog and video scene understanding technologies. The intern will collaborate with MERL researchers to derive and implement new models, conduct experiments, and prepare results for high impact publication. The ideal candidate would be a senior Ph.D. student with experience in one or more of video captioning/description, end-to-end conversation modeling and natural language processing including practical machine learning algorithms with related programming skills. The duration of the internship is expected to be 3-6 months.

    • Research Areas: Speech & Audio
    • Host: Chiori Hori
    • Apply Now
  • CV1288: Visual Reasoning and Question Answering

    • MERL is looking for a self-motivated intern to work on problems at the intersection of video understanding and visual question answering. The ideal candidate would be a senior year (>=3) PhD student with a strong mathematical background in machine learning and computer vision and who has published at least one paper in a top-tier machine learning or computer vision venue (NIPS/CVPR/ECCV/ICCV/ICML/PAMI etc.). The candidate must have prior experience in using deep learning methods for video understanding (such as action recognition, human pose estimation and tracking, etc.) and language models (such as in visual question answering or captioning). Working knowledge of generative adversarial networks will be a plus. Proficiency in Python and flexibility in using different deep learning software (TensorFlow, Pytorch, Keras, etc.) is expected. The internship is for 3-6 months with flexible start date.

    • Research Areas: Computer Vision
    • Host: Anoop Cherian
    • Apply Now
  • CV1287: Human Activity Prediction

    • MERL is looking for a self-motivated intern to work on problems related to human action recognition and anticipation. The ideal candidate would be a PhD student with a strong mathematical background in machine learning and computer vision. The candidate must have prior experience in using deep learning on human poses (2D/3D). Working knowledge of generative adversarial networks and deep learning methods for video understanding will be a plus. Proficiency in Python and flexibility in using diverse deep learning software (TensorFlow, Pytorch, Keras, etc.) is expected. The internship is for 3 months with flexible start date.

    • Research Areas: Computer Vision
    • Host: Anoop Cherian
    • Apply Now
  • CV1302: Health Monitoring from Video

    • MERL is seeking a highly motivated intern to conduct original research in the area of monitoring a person's vital signs (e.g., heart rate and heart rate variability) from video. The successful candidate will collaborate with MERL researchers to derive and implement new models, collect data, conduct experiments, and prepare results for publication. The ideal candidate would be a senior PhD student in computer vision with experience in face alignment and tracking, signal processing, machine learning, and health monitoring. Strong programming skills (C/C++, Python, Matlab, etc.) are expected.

    • Research Areas: Computer Vision, Signal Processing
    • Host: Tim Marks
    • Apply Now
  • CV1273: Exploring boosted deep networks for computer vision

    • MERL is seeking an intern with expertise in neural networks and machine learning in general to work on a project exploring the combination of boosting with deep networks for applications to computer vision problems. The ideal candidate would be proficient in TensorFlow or PyTorch and have a strong machine learning and computer vision background.

    • Research Areas: Computer Vision, Machine Learning
    • Host: Mike Jones
    • Apply Now
  • CV1283: Understanding of Deep Learning

    • MERL is looking for a self-motivated intern to work on understanding of deep learning. The ideal candidate would be a Ph.D. student with a strong background in machine learning, optimization and computer vision. Proficiency in deep learning toolbox such as PyTorch and Tensorflow is necessary. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Computer Vision, Machine Learning, Optimization
    • Host: Ziming Zhang
    • Apply Now
  • CV1268: Generative Synthetic Characters

    • MERL is looking for a self-motivated intern to work on generative approaches in machine learning for (realistic) synthetic 3D character models. The ideal candidate would be a Ph.D. student with strong background in machine learning for computer graphics. Proficiency in Python programming is necessary. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Computer Vision
    • Host: Jeroen van Baar
    • Apply Now
  • CV1269: Machine Learning for Computer Vision

    • MERL is looking for a self-motivated intern to work on machine learning for computer vision. There are several available topics to choose from. The ideal candidate would be a Ph.D. student with a strong background in machine learning and computer vision. Proficiency in Python programming is necessary. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Jeroen van Baar
    • Apply Now
  • CV1304: Uncertainty Estimation for Deep Network Predictions

    • While deep networks have been highly successful at visual regression problems such as face landmark estimation and skeleton tracking, relatively little work has been done on estimating their prediction error. We are seeking a highly motivated intern to conduct original research in the area of uncertainty estimation for deep network predictions. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The ideal candidate would be a senior PhD student in computer vision and machine learning with a strong publication record and experience in deep learning-based facial or body landmark estimation and tracking. Strong programming skills, experience developing and implementing new models in deep learning platforms such as PyTorch and TensorFlow, and broad knowledge of machine learning and deep learning methods are expected.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Tim Marks
    • Apply Now
  • CV1303: Generative Adversarial Networks (GANs)

    • Generative adversarial networks (GANs) and related methods have generated much excitement for their ability to synthesize images and data that appear remarkably realistic. MERL is seeking a highly motivated intern to conduct original research in the area of generative adversarial networks. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The ideal candidate would be a senior PhD student in computer vision with experience in GANs and related deep learning methods, as well as strong general knowledge in machine learning. Strong programming skills in Python, flexibility working across various deep learning platforms (e.g., TensorFlow and PyTorch), and previous experience coding GANs are expected.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Tim Marks
    • Apply Now
  • CV1284: Deep Learning in Computer Vision

    • MERL is looking for a self-motivated intern to work on deep learning in computer vision. The ideal candidate would be a Ph.D. student with a strong background in machine learning, optimization and computer vision. Proficiency in deep learning toolboxes such as PyTorch and Tensorflow is necessary. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Computer Vision, Machine Learning, Optimization
    • Host: Ziming Zhang
    • Apply Now
  • CV1294: Multimodal Learning

    • MERL is looking for a self-motivated intern to work on problems at the intersection of video understanding, audio/speech recognition, and language models. The ideal candidate would be a PhD student with a strong mathematical background in machine learning and computer vision. The candidate must have prior experience in using deep learning methods for video understanding (such as action recognition, human pose estimation and tracking, etc.) and language models (such as in visual question answering or captioning). Knowledge of deep learning for speech recognition and experience with generative adversarial networks will be a plus. Proficiency in Python and flexibility in using different deep learning software (TensorFlow, Pytorch, Keras, etc.) is expected. The intern is expected to collaborate with computer vision and speech teams at MERL to develop algorithms and prepare manuscripts for scientific publications. The internship is for 3 months with flexible start date.

    • Research Areas: Computer Vision
    • Host: Anoop Cherian
    • Apply Now
  • AL1031: Distributed auctions for network welfare maximization

    • We are looking for a talented individual to collaborate and facilitate research on new algorithms in mechanism design and distributed auctions. Responsibilities will include mathematical modeling, algorithm design, software prototyping, and running Monte Carlo simulations in a network traffic domain. Candidates should be strong scientific programmers and have some background in numerical optimization, simulation design, and auction theory.

    • Research Areas: Optimization
    • Host: Matt Brand
    • Apply Now
  • SP1292: Coherent Optical Imaging

    • MERL is seeking an intern to work on coherent optical imaging. The ideal candidate would be an experienced PhD student or post-graduate researcher working in coherent imaging. The candidate should have a detailed knowledge of optical interferometry and imaging with a focus on either optical coherence tomography, optical coherence microscopy or FMCW LIDAR. Strong programming skills in Matlab are essential. Experience of working in an optical lab environment would be advantageous. Duration is 3 to 6 months.

    • Research Areas: Signal Processing
    • Host: David Millar
    • Apply Now
  • SP1306: Intelligent Brain-Machine Interface

    • The Signal Processing group at MERL is seeking a highly motivated, qualified individual to join our 3-month internship program of research on stressless man-machine interface with multi-modal bio-sensors. The ideal candidate is expected to possess an excellent background in brain-machine interfaces, data analytics, machine learning, sensor design, electro-magnetic analysis, augmented reality, and sensing algorithms. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Signal Processing
    • Host: Toshi Koike-Akino
    • Apply Now
  • SP1278: Low Latency Networking

    • MERL is seeking a highly motivated, qualified intern to join the Signal Processing group for a three month internship program. The ideal candidate will be expected to carry out research on low latency networking. The candidate is expected to develop innovative low latency technology in wireless networks. The candidates should have knowledge of low latency networking such as time sensitive networking. Knowledge of wireless network standards such as IEEE 802.11 and simulation tools such as OMNeT++ is a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications, Machine Learning, Multi-Physical Modeling
    • Host: Jianlin Guo
    • Apply Now
  • SP1254: Advanced computational sensing technologies

    • The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop computational imaging algorithms for a variety of sensing applications. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/sonar imaging, or wave-based inversion. Experience with experimentally measured data is desirable. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible.

    • Research Areas: Computational Sensing, Machine Learning, Signal Processing
    • Host: Hassan Mansour
    • Apply Now
  • SP1155: Coexistence of the Heterogeneous Wireless Technologies

    • MERL is seeking a highly motivated, qualified intern to join the Electronics and Communications group for a three month internship program. The ideal candidate will be expected to carry out research on coexistence of the heterogeneous wireless technologies in the Sub-1 GHz (S1G) band. The candidate is expected to develop innovative coexistence technology for IEEE 802.15.4g to mitigate interference caused by other S1G technologies such as IEEE 802.11ah, LoRa and SigFox. The candidates should have knowledge of 802.15.4g and 802.11ah protocols. Additionally, the candidate should also be familiar with NS3 simulators. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications, Signal Processing
    • Host: Jianlin Guo
    • Apply Now
  • SP1307: Vehicular traffic environment sensing

    • MERL is seeking a highly motivated, qualified intern to join a three month internship program. The ideal candidate will be expected to carry out research on environmental sensing in high frequency bands. The candidate is expected to develop innovative sensing technologies. Candidates should have strong knowledge about neural network and learning techniques, such as machine learning, deep learning, shallow learning, and distributed learning. In addition, understanding of spectrum sensing and wireless communications technologies is necessary. Proficient programming skills with Python, Matlab, and C++, and strong mathematical analysis will be additional assets to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Signal Processing
    • Host: K.J. Kim
    • Apply Now
  • SP1252: Network Security of IoT

    • MERL is seeking a highly motivated, qualified intern to join a three month internship program. The ideal candidate will be expected to carry out research on network security for Internet of Things (IoT). The candidate is expected to develop innovative detection and mitigation technologies for abnormal security attack. The candidates should have strong knowledge about neural network and learning techniques, such as machine learning, deep learning, shallow learning, and distributed learning. In addition, understanding of wireless communications technologies, proficient programming skills with Python, Matlab, and C++, and strong mathematical analysis will be additional assets to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Signal Processing
    • Host: K.J. Kim
    • Apply Now
  • SP1158: Coherent optical transmission systems

    • MERL is seeking an intern to work on systems and subsystems for coherent optical fiber transmission. The ideal candidate would be an experienced PhD student or post-graduate researcher working in optical communications. The candidate should have a detailed knowledge of optical communications systems at the physical layer and digital signal processing for digital coherent communication, with a focus on either optical fiber communication or free space optical communication. Strong programming skills in Matlab are essential. Experience of working in a lab environment would be advantageous. Duration is 3 to 6 months.

    • Research Areas: Communications, Signal Processing
    • Host: David Millar
    • Apply Now
  • SP1305: Intelligent error correction coding

    • The Signal Processing group at MERL is seeking a highly motivated, qualified individual to join our 3-month internship program of research on error correction coding for digital communications. The ideal candidate is expected to possess an excellent background in channel coding theory, source coding, information theory, coded modulation design, signal processing, and machine learning. Strong C/C++ skill and GPU/FPGA acceleration are plus. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications
    • Host: Toshi Koike-Akino
    • Apply Now
  • SP1277: Vehicular Mobility Control Technologies

    • MERL is seeking a highly motivated, qualified intern to join the Signal Processing group for a three month internship program. The ideal candidate will be expected to carry out research on the vehicular mobility control. The candidate is expected to develop innovative edge computing technology to realize real time vehicle dynamics control. The candidates should have knowledge of the vehicular networking and control optimization. Knowledge of the Python programming and SUMO simulator is a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications, Control, Optimization
    • Host: Jianlin Guo
    • Apply Now
  • SP1147: Packet separation in IoT random access channel

    • We are looking for a qualified recent PhD graduate or PhD student to conduct research and develop novel algorithms for packet separation in IoT random access channel. The ideal candidate should have solid background in statistical signal processing and sparse recovery methods, as well as familiarity with wireless channel modeling and communications. Strong programming skills in MATLAB are required. Publication of the results produced during the internship is anticipated. The duration of the internship is expected to be 3-6 months, with flexible start date.

    • Research Areas: Communications
    • Host: Milutin Pajovic
    • Apply Now
  • SP1267: Signal spectrum analysis

    • MERL is looking for a self-motivated intern to work on signal spectrum analysis. The ideal candidate would be a senior Ph.D. student with strong background in signal processing, compressive sensing, and mathematics. Proficiency in MATLAB and Python programming is necessary. Experience in analyzing real experimental data or detecting weak signal in noisy environment is a great asset. The intern is expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Computational Sensing, Optimization, Signal Processing
    • Host: Dehong Liu
    • Apply Now
  • SP1250: Extended Object Tracking for Autonomous Driving

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in automotive radar-based extended object tracking (EOT) for autonomous driving. Previous experience on radar-based (point and extended) object tracking (extended/unscented Kalman Filtering, interacting multiple model (IMM) tracking, probability hypothesis density (PHD) filtering, etc.), data association, and jointly data association and prediction/filtering (joint probability data association (JPDA), multi-hypothesis tracking (MHT) is highly preferred. Knowledge about antenna beamforming, target detection, sensor fusion, MIMO radar, waveform modulation (FMCW and PMCW) is a plus. Familiarity with commercial automotive radar platforms is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, conduct field measurements, and prepare results for patents and publication. Senior Ph.D. students with research focuses on signal processing, machine learning, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with flexible start date.

    • Research Areas: Computational Sensing, Machine Learning, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • SP1242: Remote Sensing Data Compression

    • MERL is seeking an intern for an immediate opening, to research and develop methods for remote sensing data and image compression. The ideal candidate would have a solid background related to image or signal compression, signal processing, and information theory. The applicant should also have experience with programming in at least one of C/C++, Matlab, or Python. Experience with remote sensing data processing, such as SAR image formation, is a plus, as is familiarity with distributed coding, entropy coding, and quantization. Duration of internship is 3-6 months.

    • Research Areas: Communications, Computational Sensing, Computer Vision, Signal Processing
    • Host: Petros Boufounos
    • Apply Now
  • SP1266: Multi-spectral image enhancement

    • MERL is looking for a self-motivated intern to work on multi-spectral image enhancement. The ideal candidate would be a senior Ph.D. student with strong background in computer vision and image processing. Experience in low light image denoising and image registration is desirable. Proficiency in MATLAB and Python programming is necessary. The intern is expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Computational Sensing, Computer Vision, Signal Processing
    • Host: Dehong Liu
    • Apply Now
  • SP1180: Advanced Phased Array Antenna

    • MERL is looking for a highly motivated, and qualified individual to join our internship program of advanced phased array research. The ideal candidate should be a senior Ph.D. student with rich experience in beam forming technologies. Knowledge of wireless communication, transceiver architecture, and digital signal processing, FPGA and/or Matlab programming skills are required. RF circuits knowledge will be a plus. Duration is 3-6 months.

    • Research Areas: Communications, Signal Processing
    • Host: Rui Ma
    • Apply Now
  • SP1301: Photonic Integrated Circuits Design and Evaluation

    • MERL is seeking a highly motivated, qualified individual to join our internship program and conduct research in the area of photonic integrated circuits and Nanophotonics. The ideal candidate should have a strong background in the simulation, design, and testing of active and passive devices for optical communication, as well as deep neural network. Experience in FDTD, Matlab, Lumerical, silicon photonics, photonic, crystal, optimization algorithms, deep learning, machine learning, photonic device fabrication/measurements, and InP and silicon photonic MPW would be considered an asset. Candidates who hold a Ph.D. or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Artificial Intelligence, Electronic and Photonic Devices
    • Host: Keisuke Kojima
    • Apply Now
  • SP1251: Digital Predistortion (DPD) of power amplifiers

    • MERL is looking for a talented intern to work on the next generation Digital-predistortion algorithms for power amplifier linearization such as 5G. The development of a DPD system involves aspects of signal processing and statistical algorithm design, RF components and instrumentation, digital hardware and software. It is therefore both a challenging and intellectually rewarding experience. This will involve MATLAB coding, interfacing to test equipment such as power sources, signal generators and analyzers and construction and calibration of RF component assemblies. The ideal candidate should have knowledge and experience in adaptive signal processing, machine learning, and radio communication. Good practical laboratory skills are needed. RF semiconductor devices and circuit knowledge is a plus. Duration is 3 to 6 months.

    • Research Areas: Communications
    • Host: Rui Ma
    • Apply Now
  • DA1280: Power Market Trading Analysis and Optimization

    • MERL is seeking a highly motivated and qualified individual to join our internship program and conduct research in the area of power market trading analysis and optimization. The ideal candidate should have solid background in power markets, mathematical optimization, and stochastic analysis. Strong programming skills in Matlab, or C/C++ are required. The duration of the internship is expected to be 3-6 months, and the start date is flexible. Candidates in their senior or junior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Electric Systems
    • Host: Hongbo Sun
    • Apply Now
  • DA1297: Visuomotor Modelling for Learning Robots

    • The Data Analytics group at MERL is seeking a highly motivated intern to work on the development of dynamical models for robot learning. The target applications will be the model and control of real robotic systems with end-to-end type algorithms. The successful candidate will collaborate with MERL researchers to develop and implement new modelling techniques in high dimensional space (e.g. image space) to be used in a Reinforcement Learning framework, conduct experiments on the robots and achieve scientific contributions for publications and/or patents. Ideal candidate would be senior PhD student with experience in one or more of the following areas: machine learning modelling techniques (such as Gaussian Processes, Deep Learning) and Reinforcement Learning. Strong programming skills in Python and familiarity with ROS are expected. Previous experience in working with robotics platforms and in computer vision projects is a plus.

    • Research Areas: Artificial Intelligence, Data Analytics, Machine Learning, Robotics
    • Host: Diego Romeres
    • Apply Now
  • DA1290: 3D SLAM and Machine Learning for Drones

    • MERL is seeking a motivated and qualified individual to conduct research in 3D SLAM and deep learning for drone applications. The ideal candidate should have solid background in 3D SLAM. Knowledge of deep learning algorithms and experience working with drone testbeds is a plus. Publication of the results produced during the internship is anticipated. Duration of the internship is expected to be 3 months. Start date is flexible.

    • Research Areas: Artificial Intelligence, Computer Vision, Robotics
    • Host: Mouhacine Benosman
    • Apply Now
  • DA1279: Disaster-resilient Power Grid

    • MERL is seeking a highly motivated and qualified individual to join our internship program and conduct the research in the area of disaster-resilient power grid. The ideal candidate should have solid background in electric power systems, mathematical optimization, and stochastic analysis. Experience with Matlab or C/C++ is required. The duration of the internship is expected to be 3-6 months, and the start date is flexible. Candidates in their senior or junior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Electric Systems
    • Host: Hongbo Sun
    • Apply Now
  • DA1293: Machine Learning

    • The Data Analytics Group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2019. There are multiple opportunities for contributions. Ideal candidates would have a strong background in Generative Models with a particular interest in tractable probabilistic models for continuous variables, approximate DNN-based generative methods (ex. VAE, Boltzman Machines), Reinforcement Learning with experience in an applied setting, classical and deep machine learning methods, or time series analytics. All candidates are expected to have strong programming skills in Python and a good understanding of object-oriented programming and algorithms. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Data Analytics
    • Host: Emil Laftchiev
    • Apply Now
  • DA1289: Robot Learning

    • MERL is looking for a highly motivated intern to work on developing algorithms for robot learning. Successful candidate will collaborate with MERL researchers to design, analyze, and implement new algorithms, conduct experiments, and prepare results for publication. The candidate should have a strong background in reinforcement learning, Imitation Learning (or Learning from Demonstrations, LfD), machine learning and robotics. Prior experience of working with robotic systems is required. The candidate should be comfortable implementing the developed algorithms in Python and should have prior experience working with ROS. Prior exposure to deep learning and hands-on experience with packages such as Keras, TensorFlow, or Theano is a plus. The candidate is expected to be a PhD student in Computer Science, Electrical Engineering, Operations Research, Statistics, Applied Mathematics, or a related field, with relevant publication record. Expected duration of the internship is at least 3 months. Interested candidates are encouraged to apply with their recent CV with list of related publications and links to GitHub repositories (if any).

    • Research Areas: Artificial Intelligence, Data Analytics, Machine Learning, Robotics
    • Host: Devesh Jha
    • Apply Now
  • DA1286: Optimization Algorithms

    • The Data Analytics group at MERL is seeking highly motivated intern to work on the development of novel optimization algorithms. The target applications span a broad range of areas including machine learning, scheduling, and transportation. Successful candidate will collaborate with MERL researchers to develop and implement new algorithms, conduct experiments, and prepare results for publication. Ideal candidate would be senior PhD student with experience in one or more of the following areas: machine learning, mathematical optimization. Strong programming skills and fluency in C++/Python are expected. Prior experience with popular optimization packages such as Ipopt, Gurobi, Cplex, PyTorch is a plus. The duration of the internship is expected to be 3 months. Start date is flexible.

    • Research Areas: Artificial Intelligence, Machine Learning, Optimization
    • Host: Arvind Raghunathan
    • Apply Now
  • DA1309: Machine Learning and Optimization

    • MERL is looking for a self-motivated intern to develop predictive machine learning and optimization algorithms. Applications include time series prediction, anomaly detection, scheduling, and transportation. The ideal candidate would be a senior PhD student with experience in one or more of the following areas: machine learning, mathematical optimization, discrete-event systems modeling. Strong programming skills using C++/Python are expected. Experience with popular libraries such as Ipopt, Gurobi, Keras is a plus. The intern is expected to work with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. The duration of the internship is expected to be 3 months. Start date is flexible.

    • Research Areas: Data Analytics
    • Host: Jing Zhang
    • Apply Now
  • CD1258: Algorithms for GNSS localization

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to work on GNSS Positioning and localization. Previous experience with at least some of the GNSSs, particle filtering, interacting multiple model filtering, Kalman-type filtering, and ambiguity resolution is highly desirable. Working knowledge of C/C++ is required, and previous experience with GNSS packages such as RTKLib is highly desired. PhD and senior Master students meeting the above requirements are welcome to apply. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Control, Dynamical Systems, Signal Processing
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1261: Dynamics and Control of Electric Vehicles

    • MERL is seeking a motivated and qualified individual to conduct research on dynamics and control of electric vehicles. The ideal candidate should have a solid background in vehicle dynamics and control, model predictive control, and/or optimization. PhD students in mechanical or electrical engineering with focus on automotive systems are encouraged to apply. The intern will collaborate with MERL researchers in developing nonlinear MPC algorithms for electric vehicles. Start date for this internship is flexible and the expected duration is approximately 3-6 months.

    • Research Areas: Control, Dynamical Systems
    • Host: Claus Danielson
    • Apply Now
  • CD1256: Reinforcement learning for dynamical systems

    • MERL is seeking a highly motivated individual for collaboration on reinforcement learning with application to large-scale multi-agent systems. The successful candidate will be an advanced graduate student with extensive knowledge of reinforcement learning, preferably with experience in implementation, and preferably with knowledge of dynamics and control of large-scale systems.

    • Research Areas: Control, Dynamical Systems, Machine Learning
    • Host: Uroš Kalabić
    • Apply Now
  • CD1300: Compiler Optimizations for Linear Algebra Kernels

    • MERL is looking for a highly motivated individual to work on automatic, compiler based techniques for optimizing linear algebra kernels. The ideal candidate is a Ph.D. student in computer science with extensive experience in compiler design and source code optimization techniques. In particular, the successful candidate will have a strong working knowledge of polyhedral optimization techniques, the LLVM compiler, and Polly. Strong C/C++ skills and knowledge of LLVM at the source level are required. Publication of results in conference proceedings and journals is expected. The expected duration of the internship is 3 months and the start date is flexible.

    • Research Areas: Control, Machine Learning, Optimization
    • Host: Bram Goldsmith
    • Apply Now
  • CD1296: Optimization and Control of Thermo-fluid Systems

  • CD1298: Theoretical and computational aspects of mean-field control

    • We are looking for a graduate student intern to work on theoretical and computational aspects of mean-field control and mean-field games. An ideal candidate will be a graduate student working on MFC/MFG or Optimal Transport. Expertise in TWO or more of the following areas is required: 1). Optimal control 2). Control of PDEs 3). Geometric methods of dynamical systems theory 4). Statistical Mechanics 5). Stochastic analysis 6). Optimal Transport. Ph.D. students from top programs in engineering, physics, applied math are encouraged to apply. The duration of the internship will be 3-6 months. Publication of results is highly encouraged.

    • Research Areas: Applied Physics, Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics
    • Host: Piyush Grover
    • Apply Now
  • CD1270: Numerical Optimization Algorithms for Predictive Control

    • MERL is looking for a highly motivated individual to work on efficient numerical algorithms and applications of optimization based control methods. The research will involve the study and development of novel optimization techniques for predictive control and estimation and/or the implementation and validation of algorithms for industrial applications. The ideal candidate should have experience in either one or multiple of the following topics: convex and non-convex optimization, Newton-type optimization algorithms, numerical optimization (e.g. active-set or interior point) and optimal control. PhD students in engineering or mathematics with a focus on numerical optimization or numerical optimal control are encouraged to apply. Publication of results in conference proceedings and journals is expected. Capability of implementing the designs and algorithms in Matlab is required; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is roughly 3 months and the start date is flexible.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Rien Quirynen
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  • CD1274: Motion Planning and Experiment

    • MERL is seeking a highly skilled and motivated intern to work on motion planning and tracking control of nonholonomic systems in dynamic environments. The ideal candidate should have solid backgrounds in motion planning algorithms, their implementation, and experiment validation. Demonstrated capability in strong coding and publishing results in leading conference and journals is a necessity. Senior Ph.D. students in control, computer science, or related areas are encouraged to apply. Start date for this internship is flexible, and the expected duration is about 3 months.

    • Research Areas: Control, Robotics
    • Host: Yebin Wang
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  • CD1295: Modeling and data-assimilation of atmospheric flows

  • CD1257: Autonomous vehicles Planning and Control

    • The Control and Dynamical Systems (CD) group at MERL is seeking highly motivated interns at varying expertise levels to conduct research on planning and control for autonomous vehicles. The research domain includes algorithms for path planning, vehicle control, high level decision making, sensor-based navigation, driver-vehicle interaction. PhD students will be considered for algorithm development and analysis, and property proving. Master students will be considered for development and implementation in a scaled robotic test bench for autonomous vehicles. For algorithm development and analysis it is highly desirable to have deep background in one or more among: sampling-based planning methods, particle filtering, model predictive control, reachability methods, formal methods and abstractions of dynamical systems, and experience with their implementation in Matlab/Python/C++. For algorithm implementation, it is required to have working knowledge of Matlab, C++, and ROS, and it is a plus to have background in some of the above mentioned methods. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Artificial Intelligence, Control, Robotics
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1247: Control of Space Vehicles

    • MERL's Mechatronics group is seeking a highly motivated intern for a research position in control of space vehicles. The ideal candidate is working towards a Ph.D. in aerospace, mechanical, or electrical engineering, and has background in both optimization-based control and space vehicle dynamics. The candidate is expected to possess strong abilities in algorithm analysis and Matlab implementation. The duration of the internship is approximately 3 months. Publication of results produced during the internship is expected.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Avishai Weiss
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  • CD1260: Model Predictive Control of Hybrid Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to work on hybrid model predictive control. The scope of work includes the development of model predictive control algorithms for hybrid dynamical systems, switched systems, and quantized systems, analysis and property proving, and applications in automotive, space systems, and energy systems. PhD students with expertise in some among control, optimization, model predictive control and hybrid systems, and with working knowledge of Matlab implementation are welcome to apply. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1140: MPC-based modular control architectures

    • MERL's Mechatronics group is seeking a highly motivated intern for performing research in Optimization based modular control architectures. The ideal candidate is working towards a Ph.D. in electrical, mechanical, or aerospace engineering, or in computer science, and has background in model predictive control, optimization, set-based methods, and modular control architectures. The candidate is expected to possess strong abilities in theorem proving, and algorithm development, analysis, and Matlab implementation. The internship start date is flexible and the duration is approximately 3 months, with possible extension. Publication of the results produced during the internship is expected.

    • Research Areas: Control
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1259: Cyberphysical Automotive Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on cyber-physical vehicle systems. The research domain includes driving assistance systems, driver-vehicle interaction, connected vehicles, and cyber-security for automotive control systems. Experience with one among particle filtering, model predictive control, constrained control, distributed control is highly desired. Working knowledge of Matlab, Simulink, C/C++, rapid prototyping systems (dSPACE), and vehicle dynamics simulators is required. Experience with CAN bus is a plus. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Artificial Intelligence, Control, Signal Processing
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1255: Speed-sensorless motor control

    • MERL is seeking a motivated and qualified individual to conduct research in control of electromechanical systems. The ideal candidate should have solid backgrounds in control and estimation for electrical machines, demonstrated capability to publish results in leading conferences/journals, and experience with real-time control experiments involving high power devices. Senior Ph.D. students are encouraged to apply. Start date for this internship is around May 2019 and the duration is 3 months.

    • Research Areas: Control, Dynamical Systems, Electric Systems
    • Host: Yebin Wang
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  • MP1249: Control of Systems with Hybrid Dynamics

    • MERL is seeking an intern to develop optimal control strategies for mode-switching vapor compression systems characterized by discrete changes in dynamics. The ideal candidate has a strong background in hybrid systems, optimization, and event-based control. Proficiency in MATLAB, Python or Julia is required. Senior students enrolled in doctoral programs in engineering, applied mathematics or related fields are encouraged to apply. It is expected that the intern will assist in preparation of results for publication in scientific venues. The duration of the internship is approximately three months.

    • Research Areas: Control, Multi-Physical Modeling, Optimization
    • Host: Dan Burns
    • Apply Now
  • MP1262: Thermal modeling for electric motors

    • MERL is looking for a qualified intern to conduct research on thermal modeling and temperature estimation for electric motors. The ideal candidate should have solid background in the physics and engineering of electric machines, in particular the magnetic field calculations, and loss modeling. Related experience on control and estimation theory is a plus. The candidate is expected to collaborate with MERL researchers to conduct theoretical analysis, numerical simulations, develop algorithms and prepare manuscripts for scientific publications. Senior PhD students in electrical engineering, mechanical engineering, and other related areas are encouraged to apply. The duration of the internship is about 3 months.

    • Research Areas: Applied Physics, Dynamical Systems, Multi-Physical Modeling
    • Host: Bingnan Wang
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  • MP1263: Fault analysis for electric motors

    • MERL is seeking a highly motivated intern to conduct research in electric machine fault analysis. The ideal candidate should be a senior Ph. D student in Electrical Engineering or related discipline with a solid background in the physics and engineering of electric motors, and early fault detection. Knowledge and experience in electric motor modeling and machine learning are desired. The candidate is expected to collaborate with MERL researchers to conduct theoretical analysis, numerical simulations, develop algorithms and prepare manuscripts for scientific publications. The duration of internship is expected to be 3 months and start date is flexible.

    • Research Areas: Applied Physics, Electric Systems, Multi-Physical Modeling
    • Host: Bingnan Wang
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  • MP1248: Realtime Optimization and Control

    • MERL is seeking an intern to develop realtime optimization strategies to maximize the performance of vapor compression systems. The ideal candidate has a strong theoretical background in extremum seeking, nonlinear and adaptive control, and optimization. Proficiency in MATLAB, Python or Julia is required. Senior graduate students in engineering or mathematics programs at leading research universities are sought. The intern will collaborate with MERL researchers in developing new algorithms, conducting experiments, and preparing manuscripts for scientific publications. The expected duration is roughly three months.

    • Research Areas: Control, Multi-Physical Modeling, Optimization
    • Host: Dan Burns
    • Apply Now
  • MP1265: Detecting and localizing nanoparticles

    • MERL is searching for a graduate student to work on properties of nano-particles. Ideal candidates will have a strong background in physics (electromagnetic field) and/or imaging reconstruction algorithms. The applicant should be familiar with programming in Matlab, or Python (Python is preferred). Experience on multi-physics simulation (such as Comsol) is a plus but is not required. The expected duration is 3 months. Mitsubishi Electric Research Laboratories, Inc. is an Equal Opportunity Employer. Please see our website http://www.merl.com for information relating to our research, and http://www.merl.com/publications/ to explore our publications.

    • Research Areas: Applied Physics, Multi-Physical Modeling
    • Host: Chungwei Lin
    • Apply Now
  • MP1264: GaN and negative capacitor

    • MERL is seeking a highly motivated, qualified individual to join our 3 month internship program to carry research in the area of high power semiconductor devices and negative capacitance. The ideal candidate should have a significant background in the theory, simulation and modeling of3D high speed high power semiconductor using TCAD and fabrication experience in negative capacitor structure. Proficiency in Solid State Physics and Physics of Semiconductor theory and particularly would be a great asset. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply. The position is open from April 2017 for a duration of at least 3 months

    • Research Areas: Applied Physics
    • Host: Koon Hoo Teo
    • Apply Now