[visionlist] postdoc position in Missing Data, Domain Adaptation, and Causal Inference

[Marco Loog]

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.
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