344 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" research jobs at Nature Careers
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decisions are anticipated to be made by April 1st, 2026. Applicants must apply online at: https://www.princeton.edu/acad-positions/position/40521 Applications must be completed by January 31, 2026 at 5:00 PM
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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. The successful candidate will be employed at the Department of Computer Science of the University of Luxembourg and have access to high-performance computing resources suitable for large-scale machine-learning and
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relevant field at the time of appointment. Applicants must be U.S. Citizens, U.S. Noncitizen Nationals, or Permanent Residents at the time of appointment. Strong communication skills, a solid publication
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Experience in event planning and database management is preferred Compensation In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of the
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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we, together with a leading external pharma company party, are seeking a
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the home laboratory. Proven performance in earlier role/comparable role. Compensation In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
to antibiotics and host-like conditions. • Develop and apply statistical or machine-learning methods for interpreting single-cell and genomic datasets. • Work closely with wet-lab scientists to design perturbation
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provided) Ability to work in a fast-paced, team-oriented environment Strong organizational and communication skills Experience with cell culture is a plus Interest in learning new technologies Minimum
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming