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an outstanding track record or strong interest in the fields of antibody design, structural biology, AI/machine learning, or immuno-oncology, we invite you to apply with a project proposal for a position in our
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have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal
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projects and technical leadership. Basic Qualifications: Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related technical field. Proven experience in
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, and inclusion. The candidate will be expected to teach courses in Ecology and be able to contribute to our introductory general biology course sequences, in particular Biology 111: Unity & Diversity in
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geological field-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and climate, and topics could
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NOVA Institute for Medical Systems Biology (NIMSB) announces Four Independent Group Leader positions
for integration of large-scale omics datasets, and application of machine learning and statistical modelling for decipher cell and tissue behaviour, elucidate disease mechanisms, and enable patient stratification
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Curriculum and other under and post graduate degree programmes that involve the Faculty of Medicine. Further, they will be expected to teach in areas outside their specialisation. The successful candidate will
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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit