Connectionists: postdoc position in Missing Data, Domain Adaptation, and Causal Inference

[Marco Loog - EWI]

Missing Data, Domain Adaptation, and Causal Inference for Deep Imaging-Genetics 

We are looking for a postdoc who is interested in developing machine learning technology that can robustly cope with missing data and distributional mismatch and that can facilitate causal inference in the context of imaging and genetics data.  The candidate should have an interest both in tackling methodological questions in these areas and in applying the insights in the context of our research project on Deep Imaging-Genetics for Osteoarthritis.  The postdoc will be located in the Pattern Recognition & Bioinformatics group [Delft University of Technology], an active and lively research group consisting of researchers in pattern recognition and machine learning, computer vision, socially perceptive computing, and bioinformatics.  As part of the overarching project on Deep Imaging-Genetics for Osteoarthritis, another postdoc will be working at the Biomedical Imaging Group Rotterdam [Erasmus Medical Center] with whom we aim to collaborate closely.

We are looking for an enthusiastic postdoctoral researcher with the following qualifications and skills

- A Ph.D. degree
- Extensive experience with machine learning
- Experience with [theory of] missing data, domain adaptation and/or causal inference
- Interest in research into medical image data and genomics
- Good programming skills
- An open mind
- The desire to bridge the gap towards applications.

Please contact Marco Loog [m.loog at tudelft.nl] or Jesse Krijthe [j.h.krijthe at tudelft.nl] with any questions.
Applications should be sent to m.loog at tudelft.nl.