448 computer-science-programming-languages-"the"-"U"-"UCL"-"O.P" Postdoctoral positions in United States
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in the use of computers and software applications Demonstrated effective interpersonal, written, and oral communication skills Technical skills in the laboratory, including microscopy and
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, project management, and presentation skills Proficient with computer applications and programs associated with the position (i.e. Microsoft Office suite) Strong attention to detail and follow-up skills
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research program. The research is expected to be in one of several broad areas: statistical machine learning, statistical problems in AI, large language models, etc. Successful candidates will prepare and
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Computer Engineering Position Summary Application Deadline Applications screening will begin immediately. However, screening of applicants will continue until the position is filled. Starting date
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, computer science, or applied mathematics, and superb computer programming skills. Recommended skills include an advanced command of Python and a language in the C family. Ability and a strong desire to work in a
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of terrestrial vertebrates on Earth today with 11,000 species. A Ph.D. in Evolutionary Biology, Computational Biology, or related fields, is required. The work will focus on i) phylogenomic inference of hundreds
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needs Ensure compliance with environment, safety, health and quality program requirements Participate in the development of new ideas and projectsDeliver ORNL’s mission by aligning behaviors, priorities
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' datasets - genomics transcriptomics, and proteomics Proficiency in R, Python, and other programming languages Expertise in Linux, Git, Docker, and other high-performance computing environments Excellent
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these toolkits into biotechnology platforms and therapeutic reagents. Our research program integrates chemical biology, protein engineering, and cell biology techniques for therapeutic development, primarily in
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Computer Science, Biomedical Engineering, Bioinformatics, or a related field. Required: Strong understanding of machine learning (ML) and deep learning (DL) methods, with hands-on experience in model development and