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can read more about career paths at DTU here . Further information Further information may be obtained from professor Poul Sørensen, email posq@dtu.dk , mobile phone +45 2136 2766. You can read more
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here . Further information Further information may be obtained from Prof. Marcel A.J. Somers (majs@dtu.dk ). You can read more about Department of Civil and Mechanical Engineering at www.construct.dtu.dk
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experiments on the behavior of emerging contaminants in porous media Performing quantitative data analysis and interpretation of experimental results Working in close collaboration with modelling activities
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for the optimal candidate later dates may be negotiated. You can read more about career paths at DTU here . Further information For further information about the research at SurfCat at the Department of Physics
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training pipelines using modern ML frameworks Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity Benchmarking AI-designed recognition modules against
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diagnostic pathways. Core research tasks include planning, conducting and publishing epidemiological studies using large-scale observational data, primarily register-based, with a focus on effects of ADHD
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validation in rodent migraine models Close collaboration with computational protein engineers and clinical researchers Data analysis, manuscript preparation, and supervision of students where relevant
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generation Developing and optimizing generative models for de novo minibinder design Integrating structural biology data into AI pipelines for receptor–ligand interaction modeling Fine-tuning large protein
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publications in leading international venues. - Guiding and working with Master and Ph.D. students at ECE and collaborators as needed. More information - see the attached link or email: sshreya AT ece.au.dk
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, organoid-based models and in vivo cancer and infection models Integration and analysis of transcriptomics and proteomics datasets Establishment and maintenance of standardised experimental pipelines Data