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Previous Job Job Title Postdoctoral Research Scholar, Weed Science Program Next Job Apply for Job Job ID 58392 Location Columbia Full/Part Time Full-Time Add to My Favorite Jobs Email this Job Job
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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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the project's personalized treatment algorithms. For further information, please contact Prof. Dr. Antonio del Sol, antonio.delsol [at] uni.lu . Your profile Ph.D. degree in computational biology, bioinformatics
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Sep 2026 - 00:00 (UTC) Country Hong Kong Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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21 Mar 2026 Job Information Organisation/Company University of Basel Research Field Biological sciences » Other Computer science » Other Medical sciences » Other Researcher Profile Recognised
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 11 days ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Postdoc (f
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum