28 machine-learning-phd-in-netherland Postdoctoral research jobs at Northeastern University
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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(5%) REQUIRED QUALIFICATIONS Degree – Minimum of PhD degree in Physics, Biology, Bioengineering, or Chemistry is required, or in a field that is relatable to the Nanoscale Biophysics Laboratory’s
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expected to develop and lead projects. Ideal candidates will have knowledge of population genomics, machine learning, and evolutionary theory. Candidates should have a strong track record of publication; be
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The work heavily depends on data-driven, evidence-based modeling and collaboration with practitioners. The successful candidate will have completed a PhD (any discipline, required by start of appointment
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located in the heart of Boston. Northeastern is a leader in worldwide experiential learning, urban engagement, and interdisciplinary research that meets global and societal needs. Our broad mix
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), electrophysiology, genotyping, brain stimulation (tES, TMS), computational modeling and/or machine learning. For all our projects, we seek post-doctoral researchers who aim to take leading roles in projects
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of Boston. Northeastern is a leader in worldwide experiential learning, urban engagement, and interdisciplinary research that meets global and societal needs. Our broad mix of experience-based education
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to assist in the precise diagnosis of major diseases, including cancer and cardiovascular disease. QUALIFICATIONS: PhD in Electrical Engineering, Applied Physics, Biomedical Engineering, or a relevant field
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biomedical imaging system to assist in the diagnosis of widespread diseases, including cancer. QUALIFICATIONS: PhD in Electrical Engineering, Applied Physics, Physics, or a relevant field. Demonstrated
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to collaborative projects that explore the intersection of complex systems and public health. Qualifications PhD in a related discipline (e.g., epidemiology, applied mathematics, statistics, or network science) by