48 parallel-computing-numerical-methods Postdoctoral research jobs at Pennsylvania State University
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SPECIFICS The Uzun Lab at the Penn State College of Medicine, Department of Pediatrics, Hershey, PA, is seeking a postdoctoral scholar in Bioinformatics/Computational Biology. Our lab’s research interests
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computational skills, including numerical methods and scientific programming (Python, MATLAB, C++, etc.). Effective communication and collaborative skills. Preferred Qualifications: Experience with wide-bandgap
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hydrogen transport properties. Collaborate on neutron scattering experiments (e.g., at national labs) to investigate fluid–mineral interactions and pore structure evolution. Develop and calibrate numerical
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functional magnetic resonance imaging: fMRI) methods to investigate iconicity in spoken language – the idea that the sound of a word may convey its meaning. The successful candidate will have a PhD in a
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medicine program is a collaborative research effort that offers many opportunities for scientific interactions and advancement. Duties include (but are not limited to): Designing and executing experiments
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the College of Education, invites applications for a Teaching-Focused Post Doctoral (Post Doc) Scholar position with primary responsibilities in teaching in the Educational Psychology program within the areas
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in genome-wide computational experiments. We are part of the Center for Medical Genomics and the Center for Computational Biology and Bioinformatic s. We have strong links to Penn State College
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to the research program led by the Penn State numerical relativity group. There will also be ample opportunity to collaborate with other members of the Institute for Gravitation and the Cosmos, which includes
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on language processing studies and, in particular, on novel rehabilitation approaches to aphasia. The Sathian lab employs both behavioral and neuroimaging (functional magnetic resonance imaging: fMRI) methods
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) develop and apply statistical genomic methods to analyze multi-omics datasets for understanding complex disease etiology and (2) develop and apply novel statistical models to analyze EHR data