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://tanglab.sites.northeastern.edu/ Qualifications: Having a PhD degree from all science and engineering majors, especially Mechanical Engineering, Chemical Engineering, Physics, and Materials Science. Highly motivated. Having
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. The postdoc will join an interdisciplinary program that combines quantum sensing instrumentation, surface and interfacial chemistry, and the physics of the target systems, with current directions including
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disease areas. Preference will be given to applicants with prior training in Computer Science, Computational Biology, Computational Chemistry, and Computational Biophysics. Extensive training opportunities
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research that meets global and societal needs. Our broad mix of experience-based education programs?our signature cooperative education program, as well as student research, service learning, and global
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real and virtual agents will be a plus. The successful candidate must have a Ph.D. or equivalent degree in related engineering and science disciplines. The candidate must have progressively responsible
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engagement, and interdisciplinary research that meets global and societal needs. Our broad mix of experience-based education programs?our signature cooperative education program, as well as student research
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Health based at The Walter and Eliza Hall Institute in Melbourne, Australia. You will be part of a multi-disciplinary team that has an ambitious long term research program to decipher what factors result
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: Provides scientific and technical leadership in the management, design, and conducting of the entire research program in resilient AI within Prof. Restuccia’s research group. Responsibilities include
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research. Prepare and write research papers, presentations, grant proposals. Train Graduate Students. Qualifications: PhD in Computer Science or related field (completed or near completion) Strong
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to join the SoundMind Collaboratory and Brain Game Center for Mental Fitness and Well-being at Northeastern University. Together Seitz and Jaeggi have a broad research program that takes a lifespan approach