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Field
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data analysis, and to establish and manage a service infrastructure within the BioMS group, enabling fee-for-service access for external collaborators. You will independently design, plan and perform
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journals, and be part of a supportive and collaborative research environment at a top-tier Start Date: Determined at hire Qualifications Required Qualifications: A recent PhD (or expected PhD) in mathematics
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Temporary contract | Up to 24 months| Belval Are you
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
. Research: We develop and support a rich array of outstanding health sciences research programs, centers and resources. We provide infrastructure and opportunities for collaboration among disciplines
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given to candidates with expertise and experience with large language models (programming, benchmarking, human-centered evaluation), strong data science / computational modeling / statistical analysis
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PhD degree in Mathematics, statistics or theoretical computer science. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be
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the EU Research Framework Programme? Horizon Europe (other) Is the Job related to staff position within a Research Infrastructure? Yes Offer Description Postdoctoral Researcher in Multi-Omics, SIGN’IT
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Starting Date 15 Apr 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number #JOB5/2026 Is the Job related to staff position within a Research
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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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