42 finite-element-analysis Postdoctoral positions at Pennsylvania State University in computer-science
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analysis, factor analysis, or related methods. Experience working with dietary assessment data and translating complex nutritional exposures into epidemiologic research. Record of peer-reviewed publications
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collaboration with faculty and research staff at NCEMS, will conduct original research involving proteomics, mass spectrometry data analysis, protein interactions, protein complexes, post-translational
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prior research experience and peer-reviewed high impact factor journal publications. Prior research experience in materials characterization, testbed development, etc. will be beneficial. Priorities will
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Engineering Department at The Pennsylvania State University. This position involves the development and application of numerical analysis approaches using Machine Learning based multi-physics tools
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analysis (microscopy, spectroscopy) to investigate the fundamentals of radiation effects in electronics and shielding. Analyze data. Disseminate findings in journals and conferences and monthly presentations
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research involving large-scale public datasets, multi-omics integration, biological data harmonization, systems-level analysis, or related areas that synergize with the scientific goals, data products, and
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models, network analysis, graph-based learning, uncertainty quantification, scientific machine learning, or interpretable AI. This position is full time, on-site at the Penn State University Park campus
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required. The successful candidate will have a strong foundation in bioinformatics, biological data analysis, data integration, or systems-level analysis of molecular and cellular biology data. Candidates
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Ability to work independently and collaboratively Preferred Qualifications Experience in one or more of the following: PFAS analysis, treatment, or destruction Adsorption and activated carbon systems GC-MS
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. Preferred Experience in genomic data analysis, computational biology, statistical genetics, or functional genomics. Proficiency in R, Python, Linux/Unix, and high-performance computing environments