The internship program at MERL emphasizes close collaboration with a particular researcher or members of a small team. Primary areas of work include:
- Artificial Intelligence including:
- Machine Learning
- Computer Vision
- Speech Recognition
- Acoustic Analysis
- Data Analytics
- Cyber-Physical Systems including:
- Signal Processing
- Digital & Optical Communications
- Multi-Physical Modeling
- Planning, Optimization & Control
- Dynamical Systems
- Design of Algorithms and Semiconductor Devices
The primary intent of MERL's internship program is to provide interns with experiences that help them enhance and accelerate their professional career, while contributing to new or ongoing initiatives at MERL. Interns are exposed to relevant industrial problems ranging from speculative and exploratory research to more practical engineering tasks. Interns have a chance to become familiar with the open research culture at MERL, produce publishable work, and develop an appreciation for how breakthrough research makes an impact on future products.
MERL considers graduate students from all over the world. As many of our projects benefit from specialized knowledge in a given field, graduate students pursuing a Ph.D. typically fill the majority of internship openings.
The duration of a typical internship varies from 3 months to 1 year, with the majority of interns being employed during the summer months. As the summer is a very busy time, we encourage applications for non-summer internships and also prefer early applications for summer internships. Hiring decisions for the summer are typically made around January/February to allow enough time for any necessary paperwork (such as visa applications or other work eligibility forms) to be completed.
Boston is a fantastic city with one of the largest student populations of any city in the US. There are many social and leisure activities to get involved in, and no shortage of things to do during your stay. With close proximity to major universities such as MIT and Harvard, there are also many chances to attend seminars and lectures by well-known experts in various fields. During the summer, MERL organizes a number of social activities for interns. Some past activities included BBQ outings, whale watching and movie nights.
- Experience: At MERL, you work closely with top researchers and participate in a lab-wide R&D culture with a unique mix of curiosity-driven research and market-oriented prototyping.
- Publication: MERL is an open research lab with a strong tradition of publication in high-impact peer-reviewed venues. Internships typically aim at producing publication-worthy results and interns are co-authors on many papers each year.
- Compensation: MERL offers competitive salaries based on relevant education, skills, and work experience.
- Perks: MERL provides relocation assistance including travel costs; subsidies for commuting costs; and entertainment events for interns to get to know Boston and each other.
- Networking: Interns are encouraged to network with MERL's research staff, fellow interns, and faculty at local universities. Weekly socials and seminars provide many venues.
- Opportunity: Many MERL interns have gone on to distinguished careers at MERL. MERL research hosts have often provided letters of reference supporting their ex-interns' candidacies for jobs, fellowships, and tenure.
Publications are an important output of MERL's research, and internships often lead to one or more publications. Below is a sample listing of some recent publications that include interns as co-authors. Please visit our publications page for a complete listing of MERL papers.
- Novel deep architectures in speech processing, July 9, 2018. ,
- "Nonlinear Equalization with Deep Learning for Multi-Purpose Visual MIMO Communications", IEEE International Conference on Communications (ICC), June 2018. ,
- "Turbo Product Codes with Irregular Polar Coding for High-Throughput Parallel Decoding in Wireless OFDM Transmission", IEEE International Conference on Communications (ICC), June 2018. ,
- "Semi-Supervised Transfer Learning Using Marginal Predictors", IEEE Data Science Workshop, June 6, 2018. ,
- "Broadband SOI mode order converter based on topology optimization", Optical Fiber Communication Conference and Exposition (OFC), DOI: 10.1364/OFC.2018.Th2A.8, March 2018. ,
- "System and device technologies for coherent optical communications", SPIE Photonics West, DOI: 10.1117/12.2291869, January 2018, vol. 10560. ,