MERL is seeking a highly motivated, qualified individual to join our internship program and conduct research in the area of photonic and nanophotonic device design and optimization using deep learning. The ideal candidate should have a strong background in the simulation (such as Lumerical FDTD and MODE), design, and testing of active and passive devices for optical communications, as well as hands-on experience in deep learning (such as autoencoders and GAN using Python and Tensorflow/keras/pytorch). Experience in silicon photonics, photonic crystal, plasmonicss, optimization algorithms, machine learning, photonic device fabrication/measurements, and mask designs for 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.

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.

MERL is seeking a highly self-motivated and qualified intern to work and perform cutting-edge research in the area of Advanced RF Power Devices. The candidate is expected to have a strong technical background in Applied Physics, Semiconductor Physics and Computational Physics. Candidate is expected to carry out 3D simulation using a TCAD simulator and Matlab software. The ideal candidate should be in his/her senior year of a Ph.D. program in Electrical Engineering and/or Physics. He/she is expected to explore different 3D device architectures and using first principle physics to explain important physical mechanisms and phenomena. Candidate with knowledge in FinFET device design is desirable. The duration of the internship is expected to be 3 months with flexible starting date.