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Postdoc Associate (Interdisciplinary Humanities) Call for Applications (Cornell PhD candidates and recent Cornell PhDs) Eligible applicants for this search are Cornell University PhD candidates and
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-of-the-art pedagogy to train students who are prepared for a lifetime of learning and rewarding work. Candidates should hold a PhD or master’s degree in electrical and computer engineering or related fields
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problems in biology by combining machine learning with in-depth knowledge of biological processes. Who we are looking for You have a Master in Science (Bioengineering, Biochemistry-Biotechnology, Biomedical
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Associate (Interdisciplinary Humanities) Call for Applications (Cornell PhD candidates and recent Cornell PhDs) Eligible applicants for this search are Cornell University PhD candidates and recent Cornell
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University's Faculty of Arts and Sciences to study spatial and temporal aspects of interaction patterns in biological systems. We are looking for exceptional candidates with background in machine learning and
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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Physics, Electrical Engineering, Material Science or closely related field in hand
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facilitate scheduling machine use and also connect with vendors to ensure that equipment is well-maintained. The cell engineering facility director will play a central role in the ODBI community and research
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models