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etc; Candidates with multidisciplinary backgrounds are welcome. · Strong skills in computational and data analytical methodology development and implementation; experience in machine learning and deep
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doctoral degree in Computer Science or Biomedical Informatics or a closely related quantitative field. The successful candidate demonstrates documented expertise in machine learning and distributed
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lab’s website https://sites.duke.edu/corinnelinardiclab/ . Be You Work Performed · Perform literature reviews to guide research · Design and execution of standard in vitro assays ongoing in the lab
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of degree equivalency. Preferred Qualifications: Background in medical imaging, imaging simulation, and machine learning. Programming in Python, MATLAB, C, CUDA. Other Requirements: This position is hybrid
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QualCore partner studies include HIV, lupus, the opioid epidemic, health disparities research, and the quality and efficacy of clinical trials. More information can be found on the QualCore website: https
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the context of critical illness. This position focuses on computational modeling of host-response mechanisms using high-dimensional multi-omics datasets. The fellow develops novel computational pipelines
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the university and with industry to translate discoveries into clinical proof of concept studies. Working with a team led by Drs. H. Kim Lyerly, Zachary Hartman and Josh Snyder, this program spans basic discovery
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under Drs Ostrom and Patel’s mentorship. Be You. Requirements: The applicant should have a Ph.D. in computational biology, bioinformatics, computer science, statistics, genetic epidemiology, or a related
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to therapies and vaccines against human diseases. We are a team of highly interactive investigators that have expertise in immunology, molecular biology, virology, microbiology, structural biology, computational
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. · The appointment is viewed as preparatory for a full-time academic or research career. · The appointment is not part of a clinical research training program, unless research training under the supervision of a