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. Qualifications Required Qualifications: Ph.D. in Physics or closely related field Graduate-level (or higher) experience in an experimental laboratory Experience with analysis of astrophysical data, or related data
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pharmacy plans Healthcare and dependent care flexible spending accounts University HSA contributions Disability and life insurance Employee wellbeing program Financial counseling services Employee Assistance
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Disability and life insurance Employee wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost How To Apply Applications must be submitted
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spending accounts University HSA contributions Disability and life insurance Employee wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost
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and peer-reviewed publications in the field. Physical & Environmental Requirements • Must be comfortable working in environments that may include close contact with animals, animal byproducts, and
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wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost How To Apply Applications must be submitted online. To be considered for this position
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interdisciplinary exchange, a growing population science training program, and research support services designed to develop and nurture promising areas of new population research. Affiliates of the MPC benefit from
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and dependent care flexible spending accounts University HSA contributions Disability and life insurance Employee wellbeing program Financial counseling services Employee Assistance Program with eight
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and manipulation of synaptic function, including novel multiphoton imaging, optogenetic, and computational tools. We are looking for a highly motivated individual with a strong background in cellular
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow