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2025
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2025
Grants for access to the Gefion AI Supercomputer
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2025
Access to Gefion
Proteins in CONTEXT
Amelie Stein, Associate Professor, Ph.D., Københavns Universitet, Department of Biology
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2025
Ascending Investigator
APTOR – Reliable Analysis Procedure of Tomography-imaged Objects using self-learned Representations
Anders Dahl, Professor, Ph.D., Danmarks Tekniske Universitet
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2025
Collaborative Research Programme
Deep Learning-Accelerated Crystallography Pipeline
Andes Østergaard Madsen, Associate Professor, Ph.D., Københavns Universitet
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2025
Collaborative Research Programme
A-SOuRCCE: AI for Single-cell Omics and Reproducible Cardiometabolic and Cancer Exploration
Fran Supek, Professor, Postdoc, Københavns Universitet, Biotech Research & Innovation Centre (BRIC)
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2025
Distinguished Investigator
Pesticides and Human Health
Frederik Plesner Lyngse, Assistant Professor , Ph.D., University of Copenhagen, Department of Public Health
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2025
Emerging Investigator
Taking medical genetics studies of the Greenlandic population to a new level – with focus on cardiometabolic phenotypes (ELEVATE)
Ida Moltke, Associate Professor, Ph.D., Københavns Universitet, Department of Biology & Globe Institute
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2025
Ascending Investigator
DREAM: Differentiable Realism From AI And Modeling
Julius B. Kirkegaard, Assistant Professor, Ph.D., Københavns Universitet, Department of Computer Science
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2025
Ascending Investigator
REWIRE: Reading, Writing, and Interpreting the Rules of IDP Evolution
Kresten Lindorff-Larsen, Professor, Ph.D., Københavns Universitet, Department of Biology
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2025
Collaborative Research Programme
ADaM: Autonomous workflows for Data-driven first-principles Modeling
Line Jelver, Assistant Professor, Ph.D., Syddansk Universitet, Mads Clausen Institute
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2025
Emerging Investigator
Biologically structured deep learning for disease mechanism discovery from multi-omics and microbiome data
Manimozhiyan Arumugam, Associate Professor, Ph.D., Syddansk Universitet, Department of Clinical Research
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2025
Ascending Investigator
Chemical foundation models for small molecule detection and identification from environmental samples
Svetlana Kutuzova, Assistant Professor, Københavns Universitet, Datalogisk Institut
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2025
Emerging Investigator
Sequence and RNA structure-based predictive models for the subcellular fate of polyadenylated RNAs in degenerating and regenerating neurons
Marina Chekulaeva, Professor, Ph.D., Københavns Universitet, Department of Public Health
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2025
Collaborative Research Programme