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, Statistics, Applied Mathematics, Physics, or a closely related STEM field. Demonstrated experience developing AI and machine learning models for biomedical applications. Strong programming experience in Python
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-Doctoral Associate (9546 Post-Doctoral Associate) position. For more info on the division, visit http://www.sph.umn.edu/academics/divisions/biostatistics/. The successful candidate will work with Dr. Thierry
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C, Python, MATLAB, or similar programming languages. Experience in scientific writing and academic publishing Students in the final year of their master's programme are also welcome to apply, provided
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, acceleration, algorithms for optimal transport or generative AI). A good knowledge of Python programming (for AI, optimization) is highly desirable. Website for additional job details https://emploi.cnrs.fr
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from the following 5 core subjects: Programming with Python Embedded Systems Sensors & Actuators Measurement Technologies Analogue & Digital Electronics Develop practical teaching materials and
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: Programming 1(Python) Fundamentals of AI Data Analytics & Machine Learning Deep Learning Develop course materials and curricula aligned with international standards and industry practices in AI, machine
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qualifications and experiences needed for entry at a particular level. Find out more about the Faculty of Medical Sciences here: https://www.ncl.ac.uk/medical-sciences/ Find out more about our Research Institutes
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bioinformatics, particularly single‑cell RNA‑seq, multi‑omics, and spatial transcriptomics analysis. Specific Requirements Proficiency in Python and R; familiarity with common bioinformatics tools and pipelines
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programming languages such as R and/or Python; • Experience with widely used bioinformatics tools and frameworks (e.g., Seurat, Scanpy, SCENIC/SCENIC+, GENIE3); • Demonstrated publication record in peer
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, restructuring, and preparing datasets from multiple research sources for statistical analyses. Conducting statistical analyses using software such as R, SAS, Python, and/or Stata, under the guidance of the study