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modelling reduced‑order or low‑order modelling scientific programming (e.g. Python, MATLAB, etc.) You should be able to work independently and collaboratively, communicate your research clearly, and
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environments such as R, Java, Python, C++; Ability to communicate statistical concepts and data analysis interpretations to the group; Experience in genetic analysis of environmental exposure risk factors
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with omics data analysis, biostatistics, and image analysis tools. Strong programming skills (R, Python) and knowledge of relevant databases and pipelines. Candidates with peer-reviewed publications
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preferred: 1. Microsoft Office Applications, particularly MS Word, Excel, Powerpoint 2. Experience in R, Python The successful applicant is expected to possess at least a PhD Degree in Epidemiology, Public
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, math, statistics, and/or computer science Experience with programming, data science, and geospatial analysis (especially R, Stata, Julia, MATLAB, or Python) An enthusiasm for empirical research and an
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in Python and/or R Experience with cloud computing and high-performance computing environments Ideal Candidate Profile We are seeking a computational biologist, biostatistician or bioinformatician with
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with retrieval-augmented generation (RAG) frameworks is an advantage. Strong programming skills (e.g., Python, R, or similar). Interested applicants are invited to submit a full CV and cover letter in
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
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, with the ability to translate complex data into actionable insights. Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R) for data manipulation, analysis, and visualization
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Python, NCL, and MATLAB. Should have proficiency in scientific computing, high-performance computing (HPC), and scripting (e.g., Bash, CDO/NCO). Should have strong quantitative and analytical skills in