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Field
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research in several areas. Learning activities will focus on: The development and characterization of animal models and/or microphysiological systems for viral agents. Emphasis is placed on determining
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preferred. Proficiency in computational tools such as MATLAB, Python, R, or machine learning applications in immunology is desired. Candidates should have a PhD in Chemistry, Chemical Engineering
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, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations to biomolecular systems is a plus but not required. Applicants
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-scale human health datasets (e.g., UKBioBank, WHI, All of Us) using statistical and artificial intelligence/machine learning techniques. Develop and implement machine learning models, including
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College Station, Texas Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives
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biology, super-resolution microscopy, live-cell imaging, multi-omics, and mouse disease models to understand insulin-secretion deficiency and synapse degeneration. (See https://www.mcw.edu/departments/cell
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(data assimilation, machine learning, etc.) Writing proposals / securing external research funding Writing and submitting scientific papers Leading a research group Supervising students Participating in
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shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Continuous working with materials requiring personal
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of machine learning models for object detection, classification, and outlier detection across multiple sensor modalities. Depending on previous experience, provide scientific oversight to volunteers, students
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score derivation and validation, and other relevant analyses. Develops R or Python scripts for data analysis, statistical modeling, and machine learning techniques, ensuring reproducibility and efficiency