Postdoc position: single-cell regulatory genomics of tumor heterogeneity

Updated: 3 months ago
Job Type: FullTime
Deadline: 14 Feb 2022

The candidate will develop new deep learning solutions, including convolutional neural networks, variational autoencoders, and generative adversarial networks, to build predictive models, particularly focused on cell type diversity in cancer. These models will be used to gain mechanistic insight into cancer cell states, hence the explainability of these models (XAI) is crucial. Depending on the interest, the candidate can be involved in single-cell technology and sequencing, to collect additional data sets from mouse models, organoids, patient-derived xenografts, and human tumor biopsies from the UZ Leuven hospital.

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