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ST0349: Internship - Optical Computing and Computational Sensing
The Computational Sensing team at Mitsubishi Electric Research Laboratories (MERL) is seeking a highly motivated PhD student to conduct fundamental research at the intersection of optical computing, computational imaging, and emerging image sensors. The research will explore how optical processing and novel detectors can jointly extract useful information from light, enabling efficient sensing and inference. Potential directions include programmable optical transformations, event-based sensing, and optical–electronic systems for spatial and temporal signal processing. The intern will work closely with MERL researchers to develop physical and computational models, build and characterize experimental prototypes, and design algorithms that connect optical measurements to sensing tasks. The position offers opportunities to combine hands-on experimentation with theoretical analysis and machine learning, and to prepare results for patents and publication. The internship is expected to last 3 months, with a flexible start date.
Required Specific Experience
- Experimental optics or novel detectors: Demonstrated hands-on research experience in at least one of the following:
- Free-space optical systems using components such as spatial light modulators, digital micromirror devices, lasers, lenses, or diffractive optical elements.
- Emerging detectors and imaging systems, such as event cameras, single-photon detectors, or time-resolved sensors.
- Integrated photonic device characterization or photonic computing experiments.
- Physical and mathematical foundations: Strong understanding of relevant optics or detector physics, together with foundations in signal processing, linear algebra, and numerical methods.
- Scientific programming: Proficiency in Python, MATLAB, or equivalent tools for modeling, experimental control, data acquisition, and analysis.
- Research independence: Ability to formulate research questions, troubleshoot experiments, and communicate results clearly.
- Current enrollment in a PhD program in electrical engineering, optics/photonics, applied physics, computer science, or a closely related field.
The pay range for this internship position will be 6-8K per month.
- Experimental optics or novel detectors: Demonstrated hands-on research experience in at least one of the following:
- Research Areas: Applied Physics, Computational Sensing, Electronic and Photonic Devices, Optimization, Signal Processing
- Host: Joshua Rapp
- Apply Now
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ST0346: Internship - Generative Modeling, Inference, and Uncertainty Quantification
The Computational Sensing team at Mitsubishi Electric Research Laboratories (MERL) is seeking a highly motivated PhD student for a research internship focused on generative modeling, probabilistic inference, and optimization. Potential research directions include diffusion and flow-based generative models, efficient and controllable generation, Bayesian inference and uncertainty quantification, and generative methods for optimization. Applications may include materials and molecular discovery, inverse design, imaging, and modeling of complex physical and dynamical systems. Specific research topics will be developed collaboratively based on mutual interests and expertise. We particularly value creativity, strong mathematical and computational skills, independent thinking, and complementary expertise across disciplines. Publication of research results is expected. The internship is anticipated to last at least 3 months, with a flexible start date.
Specific Requirements:
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PhD student in computer science, applied mathematics, statistics, computational chemistry, materials science, engineering, or a related field.
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Strong research background in one or more of the following areas: generative modeling, probabilistic machine learning, stochastic processes, optimization, or computational modeling of physical and molecular systems.
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Proficiency in Python and experience with modern machine learning frameworks or scientific computing tools.
The pay range for this internship position will be 6-8K per month.
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- Research Areas: Computational Sensing, Dynamical Systems, Applied Physics, Machine Learning, Optimization
- Host: Wael Ali
- Apply Now
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ST0348: Internship - AI-Aided Fluid Modeling and Engineering Design
The Computational Sensing team at MERL is seeking a highly motivated Ph.D. student for a research internship in AI-aided fluid modeling and engineering design. The goal is to develop reasoning-driven and self-improving methods that use simulation feedback to discover and refine physical models, computational algorithms, and engineering designs. Potential directions include automated experimentation, iterative program improvement, and recursive self-improvement of modeling and optimization strategies. The ideal candidate will be a Ph.D. student in engineering, applied mathematics, computer science, or related fields with a solid background and publication record in one or more of the following areas: foundation models and agentic AI, automated algorithm discovery and refinement, scientific machine learning, computational fluid dynamics, or engineering optimization. Programming skills in Python and experience with machine learning frameworks or scientific computing tools are required. Publication of the results obtained during the internship is expected. The duration is anticipated to be at least 3 months with a flexible start date.
The pay range for this internship position will be $6-8K per month.
- Research Areas: Applied Physics, Artificial Intelligence, Computational Sensing, Dynamical Systems, Machine Learning, Optimization
- Host: Wael Ali
- Apply Now