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LevelPhD or equivalent Skills/Qualifications PhD (or equivalent) in mathematics or computer and information sciences or information and communication technology, at least 2 years of documented experience in
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(GME) training programs, as well as other National Institutes of Health T32 training programs and associated graduate programs. The appointee will partner with MCB and GME faculty to develop and co-teach
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an MD or PhD in Biochemistry, Neuroscience, Microbiology, Immunology, Genetics/Genomics, Biomedical Sciences, Biology, or a related field of study from an accredited institution or a terminal degree in
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. The interests of LABS are to develop and apply statistical, machine learning, and artificial intelligence (AI/ML) methodologies to "big data" in multi-omics and medical data for aging and diseases, such as
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unparalleled opportunities in teaching, scholarship, clinical practice and multidisciplinary collaboration. Innovative academic offerings include bachelor’s, master’s, post-master’s certificate, DNP and PhD
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in a university or college setting. Working knowledge of the content areas of probability, statistical methods, generalized linear models, statistical computing, and machine learning. Preferred
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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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a PhD in machine learning, math, stats, physics, or some other technical area by the time the position starts. Additional Qualifications Candidates should have significant experience in some area of
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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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for the university and funding agencies. Job Requirements: PhD qualification degree in Computer, Electrical or Electronic Engineering or related field At least 3 years of relevant research experience in AI security