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. Expertise with R and Linux shell is essential. Python experience preferred. Does this position have supervisory responsibilities? No Preferred Education/Experience Statistical genetics, genetic epidemiology
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biology methods, inorganic spectroscopy, metabolomics, proteomics, aqueous phase catalysis, analytical methods (mass spectrometry, NMR). Experience in data analysis and scientific programming (Python
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research, deep learning and biomedical image analysis are essential. Strong programming skills in Python and a keen interest in cross-disciplinary research are also required. Informal enquiries may be
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ethical frameworks. Proficiency in Python and experience with relevant libraries for AI/ML development. Experience with advanced AI methodologies including deep learning, transfer learning, and neural
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: Proficient with Python, R, and Linux/Unix systems. Strong skills in computer scripting and pipeline development. Experience in project management Experience in network analyses. Previous post-doctoral
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programming languages (e.g., R, Python). Successful applicants should be self-motivated, well-organized, and able to work independently and collaboratively. Excellent written and oral communication skills
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related field. Proficiency in one or more of the following: in vivo electrophysiology, two-photon imaging, animal surgery, behavioral design, programming languages (Python/MATLAB), and data analysis
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-of-the-art IT infrastructure. Ideal candidates should hold a PhD in the area of Computer Science or Electrical and Computer Engineering and have strong programming skills including Python. Past work in
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with experience in One Health or climate-health research. Proficiency in systematic reviews, survey methods, and/or causal inference is essential, along with programming skills (e.g., in R or Python
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Language Models (e.g. Llama3, and Phi4) and Commerical models (e.g. Claude 3.7 and Gemini 2.5) to develop methods for generating simulation models of healthcare pathways in Python. The Health Service