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of research investigating cancer risk and prevention. The appointee will work closely with Professor Ruth Travis, Dr Karl Smith-Byrne and other members of the research team, using large-scale epidemiological
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: Molecular modelling and simulation experience during PhD Ability to present complex information effectively to a range of audiences Experience of manipulating and visualizing large datasets We value
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framework for the joint analysis of large-scale structure (LSS) and gamma-ray data. By combining these complementary probes of the same underlying matter distribution, the project aims to sharpen constraints
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1 Sep 2026 Job Information Organisation/Company Charité – Universitätsmedizin Berlin Research Field Computer science Researcher Profile Recognised Researcher (R2) Application Deadline 11 Sep 2026
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are particularly relevant. The developed numerical models will leverage a large suite of in-situ and remotely sensed observational datasets, spanning from subsurface to atmosphere. You will have experience
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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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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contribute to the advancement of knowledge in crystalluria. We have links with The Newcastle upon Tyne Hospital groups and with large groups based in the prestigious Bernal Institute in Ireland. This project
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to manage, organize, and back up large amounts of image and tabular data generated by program and collaborator labs. Other Requirements: -May have to work on the weekend and/or after normal hours. -Travel is
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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive