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operational excellence across the post-award lifecycle. We are modernizing our systems, reimagining our service model, and investing in people and process innovation to sustain the University’s growing research
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Prince William Sound College - Cordova Extension) Online: https://www.uaa.alaska.edu/students/safety . Request a paper copy in person: UAA Police Department Office at Room 114 of Eugene Short Hall
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the full position description, including all of the required qualifications, copy and paste this link into your browser: https://mycsun.box.com/s/97zib9u6ny7c5hrv8dxxv6b8nfkp5i5x Qualifications Equivalent
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clear indication of the reference of the competition/scientific field of application and enclosing the following documents: Curriculum vitae Copy of documents supporting the academic and professional
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models. In addition, it will use Crispr-Cas9 approach to knockdown important transcription factors, such as Snail and Twist, in triple-negative breast cancer cell lines to examine the functional role and
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fundamental physical model to understand the process of fire spread for wildfires, as part of the European Research Council grant FIREMOD: (https://cordis.europa.eu/project/id/101161183 ). This is a full-time
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, modelling and simulation in CFD/FEA. Experience with scientific programming (at least Python and C++). Excellent written and spoken English. Very strong team working skills in international, interdisciplinary
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POST-DOCTORAL RESEARCH FELLOW - CEVIPOL (Centre de la vie politique) – Université Libre de Bruxelles
" Scientific knowledge and skills Candidates must have: Advanced training in quantitative methods (panel data, causal inference, multilevel modeling) Strong proficiency in R Experience with panel/time-series
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motivated individual with a background in decision analysis and simulation modeling methods who is interested in applying these tools to answer policy-relevant questions about eMTCT interventions. Our group
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datasets across broad chemical space Evaluate models through molecular dynamics, simulations, and benchmarks Active Learning in Configurational and Chemical Spaces Integrate uncertainty-aware MLFFs