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REQUIREMENTS The Tomato Genetics and Breeding Program in the Department of Plant Science at Penn State University is seeking a part-time researcher to assist with field-based tomato breeding and cultivation
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openings available. Internal Number: 362548 Required Qualifications: * Ph.D. or Masters with equivalent experience in Computational Biology, Biostatistics, Bioinformatics, Computer Science, Data Science, or
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workshops.The PhD students will focus on using state-of-the-art computational and statistical techniques to shed light on the fundamental mechanisms of decision-making.We are particularly interested in candidates
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 12 days ago
for highly-motivated and qualified candidates to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting
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– with prior experience working with administrative data. Advanced skills in database management (i.e., SPSS,Excel) as well as advanced analytic approaches (i.e.,multivariate statistics) are required. SQL
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– with prior experience working with administrative data. Advanced skills in database management (i.e., SPSS,Excel) as well as advanced analytic approaches (i.e., multivariate statistics) are required. SQL
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the context of computing Familiarity with research tools and methods, including statistics platforms like R and/or thematic analysis Knowledge of user-centred design and research methods involving human
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, Pennsylvania 19004, United States of America [map ] Subject Areas: Mathematics Industrial Engineering Economics Statistics Management Science & Engineering (more...) Computer Science and Electrical Engineering
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Skip to main content Recruit Home Open Recruitments Visiting Researcher (JPF10537) Visiting Researcher Apply now to Visiting Researcher Job #JPF10537 Computer Science / Henry Samueli School Engr & Ap
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informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world