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requirements). Qualifications: Doctoral degree completed (or near completion) in Civil Engineering, Structural Engineering, or a closely related field at the time of application. The degree must be completed by
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of the relevant fields. Preferred skills Knowledge of food chemistry, food engineering, biochemistry, and plant physiology. Knowledge and/or experience in purification, characterization, modification, and structure
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The Nuclear Science and Engineering Division at Argonne National Laboratory seeks a Postdoctoral Appointee to conduct R&D on metallic materials for extreme environments relevant to nuclear energy
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further advancing the science and technology of additive manufacturing (AM). CAAAM involves a multi-disciplinary team of researchers from materials science, mechanical engineering, manufacturing, data
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: Postdoctoral Researcher - College of Engineering Position Type: Faculty Location: Villanova, PA Recruitment Type: Internal/External Applicants Work Schedule: full-time/12-months Department: 959-Center for Energy
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
connections between wet and dry lab, bringing together computational biologists building new methods at the interface of structural biology and machine learning and experimentalists studying how proteins
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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than
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-disciplinary environment? Information Many of the most challenging problems in science and engineering involve physical systems that evolve over time while exhibiting rich mathematical structure. Fluid flows
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. About You You will have a PhD in computational engineering, applied mathematics, bioengineering, mechanical engineering or a related discipline, with strong experience in CFD or numerical simulation. You
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fundamental algorithms for producing policies for rich goal structures in MDPs (e.g. risk, temporal logic, or probabilistic objectives), and modelling robot decision problems using MDPs (e.g. human-robot