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mathematics and engineering. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit and state
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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outside Duke University. Preferred qualifications: PhD (completed in the last 1-5 years or PhD candidate) in a quantitative discipline, including Computational Biology, Bioinformatics, Computer Science
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genomics, metabolomics, or microbiome analysis Computer science, particularly machine learning, artificial intelligence, data science, or computational biology Mathematics or statistics, with experience in
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regarding the use of lasers, chemicals, infectious agents, animals, and human subjects, as needed. Requirements: PhD Duke is an Equal Opportunity Employer committed to providing employment opportunity without
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projects currently under grant support. Required Qualifications at this Level Education/Training PhD Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard
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Preferred Qualifications: A PhD or MD/PhD (or equivalent) in biological sciences (cell & developmental biology or a related field) which was awarded not more than 18 months ago. Evidence of successful
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automation tools for academic and translational applications. Required Qualifications at this Level Education/Training PhD Duke is an Equal Opportunity Employer committed to providing employment opportunity
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Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency. 1. A candidate may also be appointed to a postdoctoral
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to mentor students, teach/train other researchers in LCA tools, and develop independent research projects as desired. The successful applicant will possess a PhD in chemical engineering, chemistry