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Field
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Associate: Physics and Astronomy. Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in High Energy Physics or a closely related field in hand by the start
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, Matlab Preferred Qualifications: Experience in thermos-fluids in porous media. Experience in High-Performance Computing (HPC) on CPU or GPU platforms. Experience in mentoring of graduate and undergraduate
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high stress situations Work performed in indoor and outdoor environments. Exposure to noise, distractions, unpredictable behaviors, and/or to bio-hazardous material. May be required to maneuver items
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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. Experience working in a Linux environment preferred. Experience working in high-performance computing environments preferred. Experience working with NCBI dbGaP, TCGA, COSMIC data preferred. Training in
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analyses. In addition, experimental and computational abilities for large datasets are highly desirable. The applicant must be able to comply with high standards of work ethics, regulations and rules
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commensurate with their essential status should be afforded, independent of the postdoc's source of funding. Responsibilities: Perform advanced computational analyses on longitudinal brain imaging and behavioral
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based on satisfactory performance. Teaching duties will include Weather and Climate (METR 100, repeated each semester), Severe and Unusual Weather (METR 140), Atmospheric Thermodynamics (METR 223), and a
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Job Description This position offers a unique opportunity to work on advanced projects at the intersection of AI, machine learning, computer vision, and multimodal learning, focusing on advancing