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Join a research environment where Artificial Intelligence and Machine Learning moves beyond theory into clinical impacts. At the Faculty of Engineering and Science, this postdoctoral position offers
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the Grand Canonical ensemble and machine learning is required. A solid record of publication in peer-reviewed journals is expected. Excellent verbal and written communication, interpersonal, and
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to collaborate with other team members, such as the Research Fellow who focuses on building machine learning models for perceptual quality prediction. About you The post-holder is expected to have a PhD degree (or
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UiO/Anders Lien 16th July 2026 Languages English English English PhD Research Fellow in AI for Rehabilitation and Motor Learning Apply for this job See advertisement About the position We invite
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Nutrition Postdoc Appointment Term: Fixed term for one (1) year with opportunity for renewal Appointment Start Date: ASAP Group or Departmental Website: https://colmanlab.stanford.edu/(link is external) How
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) seeks to recruit a post-doctoral associate to join a new initiative focused on designing and developing a machine perfusion system to improve organ preservation. The candidate will work in a dynamic
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focuses on detecting underwater acoustics using AI methodologies. Additionally, CFD simulations combined with physics-informed machine learning will also be examined. Several research and industrial
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required OBGE, SOM and TGS computer systems, software, databases, and other tools to complete documentation, scheduling, and reporting of PhD student milestones with program DGSs, including course
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to contribute to the MPH infectious diseases concentration curriculum, teach graduate and undergraduate courses in infectious disease epidemiology and their specific area of expertise, commit to exemplary
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PhD in Computational Simulations of Turbulent Reaction Flows for Clean Energy and Sustainable Propul
machine-learning methods, you will analyze flame-turbulence interactions, pollutant formation, as well as unclosed terms relevant to LES modeling. The analysis involves the fluid dynamic as