ESR1 will work on “Machine Learning for Biological Network Analysis” with Karsten Borgwardt at ETH Zürich in Basel, Switzerland.
ESR2 will work on Machine Learning and Causal Inference to Optimize Genomic Interventions using Disease State Representations with Caroline Uhler at ETH Zürich in Basel, Switzerland.
ESR3 will work on “Comparison of heterogeneous or uncertain network structures” with Kristel Van Steen at University of Liege, Belgium.
ESR4 will work on methods for subtype detection in high-dimensional data with a special focus on longitudinal data with Bertram Müller-Myhsok at the Max Planck Institute of Psychiatry in Munich, Germany.
ESR5 will work on “Deep representations of somatic mutations and germline variants for cancer Research” with Bernhard Schölkopf at the Max Planck Institute for Intelligent Systems in Tübingen, Germany.
ESR6 will work on “Clinical decision support for precision medicine” with Tobias Heimann and Volker Tresp at Siemens Healthcare GmbH in Erlangen, Germany.
ESR7 will work on “Methodology for discovery and validation of omics-based predictors for follow-up data in large population-based biobanks” with Krista Fischer at the University of Tartu in Tartu, Estonia.
ESR8 will be “Predicting patient trajectories and outcomes from national level data” with Jaak Vilo, Meelis Kull and Sven Laur at STACC Ltd in Tartu, Estonia.
ESR9 will work on “Machine learning for the discovery of new functional and regulatory gene networks” with Joaquin Dopazo at Fundación Pública Andaluza Progreso y Salud in Sevilla, Spain.
ESR10 will work on “Personalized health trajectories” with Antonio Artés at Universidad Carlos III de Madrid in Madrid, Spain.
ESR11 will work on learning from multi-modal data to improve cancer treatment with Chloé-Agathe Azencott at ARMINES/Mines ParisTech in Paris, France. For a more detailed description, see: http://cazencott.info/dotclear/public/offers/phd_proposal_mlfpm_esr11.pdf
ESR12 will work on “Integration of multi-omics data and disease-related phenotypes for better disease risk prediction” with Florence Demenais at the University Paris Diderot, in Paris, France.
ESR13 will work on “Visualization of Deep Learning on Biomedical Data for Improved Interpretability” with Magnus Fontes at Qlucore in Lund, Sweden.
ESR14 will develop and apply causal inference methods to high dimensional healthcare data with Michal Rosen-Zvi at the Healthcare Informatics Department in IBM Research – Haifa, Israel. See https://www.research.ibm.com/haifa/dept/vst/analytics.shtml for more details.