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situations where numerous and diverse demands are involved. Skill in the research, development and evaluation of policies and programs, including skill in the collection, evaluation, and interpretation of data
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optimization code used, particularly for automated transition state searches. • Perform molecular dynamics simulations to estimate thermodynamic/macroscopic properties. IPREM brings together over 300 staff
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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numerical simulations will also be required to evaluate them. The scientific results will be published as articles in proceedings of high-level international conferences (IEEE Globecom, ICC, SPAWC, etc.) and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 2 months ago
-discipline to carry out research independently # Willingness to work on numerical and experimental tasks # Programming skills (e.g., Matlab, SIMULINK, Python) or other common process simulators # Excellent
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have recently completed or be in the final year of your master’s degree in Physics or Optical Engineering. Additional requirements A very good knowledge in developing numerical simulation tools such as
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studies fundamental and applied aspects of multiphase flows, combining advanced experiments and state-of-the-art numerical simulations. Research focuses on dense dispersions, turbulence interacting with
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the following documents: a) Application minute for the competition addressed to the Rector of the University of Aveiro; b) Copy of detailed curriculum vitae structured according to the items under point 5; d) Any
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Position overview Position title: Moore Postdoctoral Fellow Salary range: A reasonable salary range estimate for this position is $69,073 - $71,632. The posted UC academic salary scales (https
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specimens. The postdoc will contribute to the development of hybrid modeling and identification approaches that combine classical constitutive frameworks, numerical simulation, and machine learning. The work