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Field
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Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus. Candidates should apply at: https://puwebp.princeton.edu/AcadHire
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and Knowledge: Strong interest in (or be already skilled in) the development, application, and testing of hydrologic models. Comfortable with working in the python programming language. Knowledge and
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Python and machine learning frameworks (e.g., PyTorch, Jax, scikit-learn) applied to genomic/related datasets. Experience with sequence modeling architectures and interpretable AI methods (SHAP, Integrated
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engineering pipelines. Implement models in Python using frameworks such as PyTorch, TensorFlow. Perform statistical analyses and model benchmarking against existing methods. Collaborate with wet-lab scientists
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. Experience in Python code, Matlab, and LabChart. Knowledge of cardiovascular physiology. Department Contact for Questions Miranda Lockwood, SHRM-CP Human Resources Business Partner mjlockwo@iu.edu Additional
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degree in physical sciences, biochemistry, or computer science is required at the start of the position (we accept ABD applicants). Applicants with prior experiences with Linux command line, Python
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data analysis skills, including experience with R, Python, MATLAB • Excellent written and verbal communication skills • Strong organizational and interpersonal skills and ability to work collaboratively
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. Basic proficiency in using Python and/or command line interface (CLI). Basic understanding of raytracing and optical design. Experience with SharePoint, SolidWorks PDM vault, GitHub. Required Documents
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advanced analytical skills including statistical programming in Python, Stata, R, and/or SAS • Excellent communication and presentation skills • An ability to work both independently and in teams Benefits
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the data from HEP experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability