57 machine-learning "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" Postdoctoral research jobs at Nature Careers in United States
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portal (https://jobs.vib.be/apply/130479 ) before 28 February 2026. Please, provide your CV, 2 reference contacts and a motivation letter.
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. degree and is determined by the Graduate College (https://grad.uiowa.edu/postdocs/salary). Applicants must be eligible to work in the United States. Required Qualifications: Completion of Ph.D. or M.D
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teaching, research, and service mission. Apply online at https://psu.wd1.myworkdayjobs.com/PSU_Staff/job/College-of-Medicine/Postdoctoral-Scholar---Pediatrics_REQ_0000074211-1 CAMPUS SECURITY CRIME
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biology and publication records (minimum of one-first author publication in a peer-reviewed journal) are encouraged to apply for the open position ( https://talent.stjude.org/postdoc/jobs/JR1859 ). St. Jude
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) Experience in genomics, single-cell data, or machine learning (preferred) Why this is exceptional Build next-generation AI models of the human genome Work with one of the richest longitudinal PD datasets
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Requirements: * A brief, one-page description of project; we encourage a graphical abstract *Cover Letter * CV * Brief letter of support from Princeton faculty mentor (one page) Apply at https
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Project Description: Drug toxicity and resistance are the leading causes of therapeutic failures. The Chen Lab (https://www.stjude.org/research/labs/chen-lab-taosheng.html) studies: (1) the chemical
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vitae, a brief cover letter outlining their research experience and interests, and contact information for three references via email to: sgong@engr.wisc.edu Research Group Website: https
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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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