DDSA PhD Fellows 2023
Meet the 10 new DDSA PhD Fellows and watch them explain their research projects in the videos below!
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Arman Simonyan
University of Copenhagen
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Research Project
New Machine Learning-Driven Approaches for Peptide Hormone and Drug Discovery
Arman holds an MSc in Bioinformatics
Asbjørn Munk
University of Copenhagen
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Research Project
Towards Theoretically Grounded Domain Adaptation for Brain Image Segmentation
Asbjørn holds an MSc in Computer Science
Christoffer Sejling
University of Copenhagen
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Research Project
New Methods for Functional Data to Quantify Clinically Relevant Traits of CGM (Continuous Glucose Monitor) Measurement Patterns and Guide Clinical Decision Making
Christoffer holds an MSc in Mathematical Statistics
Jakob Lønborg Christensen
Technical University of Denmark
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Research Project
Diffusion Models for Image Segmentation
Jakob holds an MSc in Mathematical Modelling and Computation
Javier Garcia Ciudad
University of Copenhagen
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Research Project
Modelling Electrophysiological Features of Sleep and the Variation Induced by Differences in Species, Gender, Age, or Disease Using Deep Learning
Javier holds an MSc in Human-Centered AI
Jette Steinbach
Aarhus University
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Research Project
The Impact of Genetic and Environmental Heterogeneity on Health Prediction Models
Jette holds an MSc in Statistics
Mikkel Runason Simonsen
Aalborg University
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Research Project
Improving the Clinical Utility of Prognostic Tools through Calibration
Mikkel holds an MSc in Mathematics
Mikkel Werling
University of Copenhagen
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Research Project
Increasing Predictive Performance and Generalizability of AI in Healthcare Using Meta-learning and Federated Learning in an International Collaboration
Mikkel holds an MSc in Cognitive Science
Sebastian Loeschke
IT-University of Copenhagen
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Research Project
Tensor Networks for Efficient Image Rendering
Sebastian holds an MSc in Computer Science
Thomas Gade Koefoed
University of Copenhagen
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Research Project
Resolving Insulin Resistance Heterogeneity in Human Skeletal Muscle Using Multimodal Single-nucleus Sequencing
Thomas holds an MSc in Bioinformatics