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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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these processes. The successful candidate will work with animal models and clinical samples and will apply a range of cutting-edge techniques, including flow cytometry, 3D microscopy and transcriptomic analyses
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, the results from these methods and supplementary measurements will enable the modeling of groundwater flow within the various aquifers. This modeling work will be supplemented by field visits to gather new data
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independently. Among the key duties of this position are the following: Designs, discusses, and performs diverse experimental models and techniques related to the study of innate cells. Contributes to general
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 2 months ago
substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and
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inflammation and disease. Using patient samples and advanced human models including patient-derived precision-cut liver slices, you will explore the immunological effects of real-world plastic exposures. With
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of the meiotic cell cycle. Our work involves genetic mouse models, combined with molecular, cellular, and biochemical analyses. A successful candidate will work closely with the principal investigator as
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) for catchments in Germany. This includes implementing and validating specific components (the weather generator nsRWG and the hydraulic model RIM2D) and running the entire model chain for current and future
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substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required