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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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; contribute to the mentoring of trainees within the lab; publish peer reviewed manuscripts and contribute to funding proposals. Educational Requirements • PhD in Chemistry, Bioinformatics, Computational Biology
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, Duke University Biology Department to study how archaeal microbial communities respond to stress in hypersaline environments. A PhD in computational and/or experimental biology is required in fields
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and revision Educational Requirements: Work requires a PhD (bio)statistics, econometrics, data science, or related field. Experience/Skills Required: A background in commonly used programming
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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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. Qualifications: Qualifications include a PhD or equivalent in environmental health, epidemiology, biostatistics, or a closely related discipline. The successful candidate should be highly organized and have
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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