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requires expertise in host-microbe interaction modeling, computational biology, and biological network modeling, with a strong focus on applying machine learning to analyze and interpret complex systems
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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California Health Sciences University - College of Osteopathic Medicine | Clovis, California | United States | 14 days ago
curriculum utilizing team-based learning (TBL) and active learning modalities Essential Duties: All faculty are expected to contribute to the teaching load of the Department which he/she holds an appointment
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practical knowledge and skills in cutting-edge information technologies. Focusing on innovation and experiential learning, we prepare students at all levels, including PhD, Master, and undergraduate
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be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD awarded in Electrical or Computer Engineering Knowledge about Deep Learning
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-cultural. EPFL covers a wide spectrum of science and engineering and offers a fertile sSchool of Basic Sciences include theoretical and experimental biophysics, biological imaging and physics of machine
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the broad landscape of computational science, including artificial intelligence, machine learning, deep learning, and their applications in addressing complex scientific and societal challenges, encompassing
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techno-economic assessments is preferred, and knowledge of applied computational techniques and machine learning methods is a plus. Postdoctoral research experience is preferred but not essential. A
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spoken German/ willingness to learn German Computer skills: MATLAB and/or R desirable You are motivated and self-propelled You are flexible and creative You should be a team player with high social skills
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plan as well as teach within the Advanced Nursing Practice and/or Entry to Baccalaureate Nursing Practice Divisions. The successful candidate will become a valued faculty member of the Division