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researchers. Exciting opportunities also exist to work with faculty from MD Anderson Cancer Center, Rice University and UTHealth School of Biomedical Informatics. Job Duties Analyzes large data sets. Analyzes
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scientist who is excited to develop computational approaches with wide applicability in the life sciences. You should hold a PhD degree in computer science or physics and should have a strong background in
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should have a PhD degree or equivalent and should have a strong background in coding and AI approaches. Degree in computational science, neuroscience or related fields is preferable. Familiarity with brain
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Postdoc in CRISPR Meta-Analytics and AI for Therapeutic Target Discovery and Priotisation (OT Grant)
(obtained at the call closure time or near completion) in a relevant subject, e.g., bioinformatics, computer science, mathematics, physics, engineering or a related field of science. Proven track record
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. and globally. Qualifications: A doctoral degree (PhD and/or MD) completed or pending in quantitative discipline (Bioinformatics, Computer Science, Statistics, Applied Mathematics, etc.) is desired with
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)automated data processing and a collaborative workspace. Eligibility requirements: PhD or equivalent degree in Computer Science, Physics, Life Sciences, or related field. Strong background in developing AI
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methods to build a classifier based on mRNA and WES profiles Your profile: PhD / PostDoc applicants should hold a MSc/PhD in computer science, physics, mathematics or a related discipline strong Knowledge
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About the German Cancer Research Center (DKFZ) The German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) is Germany’s largest biomedical research institute and a member of the Helmholtz Association of German Research Centers . Over 3,200 staff members from 88 nations are...
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positions based on performance and funding. Qualifications: A Ph.D. (or equivalent) in electrical engineering, biomedical engineering, computer science, medical physics, or a related field is required
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to application of machine learning and data mining techniques to analyze multiple data modalities related to corneal disease, including imaging, genetic and clinical data. Qualifications PhD in Computer Science