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Previous Job Job Title Post-Doctoral Associate - Computational Health Sciences Division Next Job Apply for Job Job ID 360487 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular
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-disciplinary research team, consisting of researchers in coil development, electromagnetic simulation, parallel transmit RF pulse design, pulse sequence development, advanced MR image processing, analysis and
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development, data management, and preparation of scientific reports (20%) Computer knowledge to enter data from experiments into existing databases; spreadsheets and web-based applications. Conduct background
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team of undergraduate/postgraduate researchers. Candidates should be able to multitask parallel evolution experiments with phenotypic and genomic analyses. Job Duties and Responsibilities: Typical tasks
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the collective behavior of complex systems, understanding how micro- level interactions drive macro-level evolution. Practical experience with high-performance computing (HPC) and parallel processing to enable
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multiphase flow in porous media. 80% - Applying numerical and analytical infiltration models to quantify groundwater recharge potential under varying hydrogeologic conditions. In parallel, the researcher will
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Pediatric Clinical Behavioral Neuroscience- Birth to Three Program Our fellowship program aims to prepare postdoctoral
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computational mechanics, FEM/Particle methods, time integration and analysis (60%); -help to write quality research proposals to government agencies and industry, prepare/assist in journal research papers/book
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) program. The role offers opportunities for professional development, including leading large-scale analyses with advanced statistical methods and leading manuscript preparation to enhance your research
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Qualifications Ph.D. in Genetics, Computational Biology, Bioinformatics, Agronomy, Horticulture, or related field in genome analyses Demonstrated experience in population genetics using genome-wide SNP datasets