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“Research for a life without cancer" is our mission at the German Cancer Research Center. We investigate how cancer develops, identify cancer risk factors and look for new cancer prevention strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients...
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Sciences | College Administration Natural and Mathematical Sciences The Post Doctoral Scholar will play a key role in advancing interdisciplinary research in STEM higher education to evaluate student
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energy system optimization and control Engineering, Applied Mathematics or a comparable quantitative discipline Very good software development and data analysis skills Inquisitive and passionate about
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-doctoral researcher with a strong quantitative background in biology, evolution, or social science, and previous experience in mathematical modeling or behavioral experimentation. Purpose: Complete a multi
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Department: Ctr for Nuclear Rec & Cell Sig Salary: Commensurate with experience Description: The Center for Nuclear Receptors and Cell Signaling in the College of Natural Sciences and Mathematics
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Requisition Id 14907 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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Engineering, Computer Science, Applied Mathematics, or related fields Strong background in control systems, machine learning, and scientific computing Programming proficiency and experience with simulation
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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is
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: Experimental condensed matter physics, cosmology and astrophysics, particle astrophysics and dark matter, high energy, atomic, pulsar and biophysics; theoretical cosmology, condensed matter, mathematical, and
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance