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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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Python, MATLAB, or C++. Experience with machine learning techniques, CAD, computational modeling, 3D printing, motion capture, and/or material testing. Proficiency in programming languages commonly used in
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pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings. Coordinate the collaboration between the chronobiology lab (led by Dr. Paul Petrus) and the
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Materials A single PDF or Word document containing a resume, letter of interest, and a list of three (3) professional references is required to apply. Important Instructions: When prompted to upload your
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(e.g., python, tcl) The candidate will also help with mentorship and training graduate and undergraduate students. The terms of employment, which would be a year, with a possibility of renewal, include a
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quantitative biomedical sciences. Experience with R and/or Python packages Experience working with Linux, including shell scripting Preferred Qualifications: PhD or MD/PhD degree in Bioinformatics, AI machine
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interpretation through deep learning model development using Python and MATLAB. Why should I apply? Under the guidance of a mentor, you will engage in a variety of research activities, including: developing
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advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases (e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux
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such as python. Experience with HPC environments and linear algebra. Demonstrated ability to conduct independent research and publish in peer-reviewed journals. Position Details : Location: College
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in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch). Experience with bioinformatics tools and genomic data analysis. Strong programming and data analysis skills. Excellent