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. Proficiency in Python programming and major ML/DL frameworks (e.g., PyTorch, TensorFlow). Solid understanding of optimization and regularization methods for training complex neural networks. Practical knowledge
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, using R or Python; experience with these datasets is helpful but not required Preparing statistical reports and presentations Presenting findings at regional or national scientific meetings Mentoring
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. Intermediate to advanced skills with at least one statistical and/or programming software (e.g., R or Python) and with regression modeling methodologies are required. Experience working with large administrative
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genetics. Proficiency in one or more programming languages (e.g. R, python), common analytic tools for genetic research (e.g. PLINK, SAIGE, imputation, etc.), and a Unix-based computing environment is