395 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" research jobs in Norway
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-working candidate. Main responsibilities Develop and apply machine learning and statistical modeling techniques, including novel AI architectures, for the analysis of complex traits and precision prediction
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an agent-based computer model of decision-making in social ecological systems, and part of the work be working with stakeholders to refine the tool and test out a range of uses for it. The Research
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, and relevance for the AI centre and Work Package 2. The department will host an online orientation meeting for the position 8 January 2026 at 14.00 hrs (CET). Participate at: https://uib.zoom.us/j
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at 14.00 hrs (CET). Participate at: https://uib.zoom.us/j/62281498137?pwd=Qakqii2iD8DxRLgrArHcugDrNKyEbW.1 Project proposal: The artistic research project proposal should place the project in a subject
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exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: The average grade point for courses included in
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leader will be Professor Jonathan Robert Whitlock (read more about the group at: https://www.whitlocklab.org/). About the project The successful candidate will perform large-scale neural recordings in
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mediators using in vivo mouse models. The position has a duration of two years. The project group is part of a vibrant and inclusive research environment (https://www.ous-research.no/kt/) at the Department
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machine learning and AI techniques to improve prediction of contaminant transport, sediment dynamics, and ecosystem exposure in complex fjord environments. The research will benefit from extensive
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position as Postdoctoral Fellow in law at the UiS School of Business and Law, Department of Accounting and Law. The Postdoctoral Fellow will be affiliated with the research project AUTO-MARE – Autonomous
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modelling tools. This PhD position aims to achieve to develop by the use of automatic picking, rather than manual, travel time picks, and the application of machine learning methods to reliably pick relevant