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, or machine learning. Proficient in programming languages such as Python, C++, and MATLAB. Strong publication record in relevant research areas. Excellent communication and teamwork skills. Modes
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biological mechanisms utilizing U-M Core Facility resources. Experience in Python or R programming is highly preferred. Mission Alignment: Candidates must demonstrate a clear interest in ecology and species
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doctoral degree in epidemiology, biostatistics, bioinformatics, microbiology, or a related field Strong quantitative and statistical skills, with proficiency in R or Python Experience working with
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and statistical skills, with proficiency in R or Python Experience working with longitudinal data, infectious disease epidemiology, or high-dimensional datasets Demonstrated track record of peer
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Qualifications* Experience with mass spectrometry (especially DIA) and proteomics applications. Strong programming skills (Python, Java) with proficiency in a Linux environment. Experience with computational
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systems or autonomous AI frameworks · Solid foundation in computational biology · Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX) · Strong analytical, problem solving, and communication
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in collaborative research projects. Publish manuscripts in peer-reviewed journals. Experience with mass spectrometry (especially DIA) and proteomics applications. Strong programming skills (Python
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Knowledge of SAS, R, Python, and SQL, or data visualization software Knowledge of open/public/private databases HOW TO APPLY: Applicants should submit a letter of interest, curriculum vitae (CV), name
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: language learning/acquisition, interpretability/mechanistic analysis, human-like modeling, or formal language theory Excellent programming and data analysis skills (Python required; familiarity with PyTorch
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-on experiences in software design and implementation using Python, C/C++, and Matlab, under Windows and Linux environment, Strong communication skills, and ability to work independently and with