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Field
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/postdoctoral-researcher-on-hyb… Requirements Research
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learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and Africa. UM6P is an
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statistical and machine learning methods, particularly for high-dimensional or longitudinal data. Demonstrable experience in research software development using R or Python and a track record of contributing
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. The Postdoctoral Associate will work under the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB
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on improving mental health and wellbeing in rural, coastal, and underserved communities across Lincolnshire. This post is permanent and full-time (1.0 FTE) and offers the opportunity to develop an independent
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supervision, practical supervision, and development of course materials, where multiple types of experiences are preferred. Practical experience with GIS software, e.g. ArcGIS and QGIS. Experience with
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Postdoc position in method development in human statistical genetics, with a focus on classificat...
complex traits. Dr Speed has developed the software package LDAK (www.ldak.org ). The position will be mainly funded by an ERC consolidator grant, aimed at finding novels ways to classify complex diseases
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. -Global (SM)EFT interpretation of LHC (Higgs, top, diboson, etc) and other measurements -Improvement/extension of the SMEFT framework ; development of a consistent uncertainty model ; studies of limits
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modeling; and theory-grounded guarantees for proposed algorithms. Collaborate with scientific users and experimentalists at DOE experimental facilities to apply the developed software to real datasets and