-
The Faculty of Science invites applications for a POSTDOCTORAL RESEARCHER IN MACHINE LEARNING FOR NATURE CONSERVATION starting from August 2025 or as agreed. The Postdoctoral Researcher will be
-
. We require the candidate to have documented experience in either large-scale genomics data analysis with computational or approaches/biostatistics, or machine learning/deep learning. Experience with
-
full-time, three-year fixed-term contract starting in September 2025 (or later by agreement). The position includes a six-month trial period. Postdoc applicants must hold a doctoral degree by the start
-
of large-scale genomic data sets is a requirement for this position. Experience with data integration, machine learning, network science, cancer biology, and/or gene regulation is considered an advantage
-
dysfunction. An ensemble of multi-scale computational approaches (molecular dynamics simulations, quantum chemistry, machine learning) are applied to study the mechanistic aspects of biomolecules in great depth
-
strong publication record and a solid background in computational RNA biology, particularly in alternative splicing regulation, are our top priorities. Expertise in machine learning and human omics data
-
, are our top priorities. Expertise in machine learning and human omics data analysis is highly advantageous. The ideal candidate should demonstrate a high level of independence while also valuing
-
, are our top priorities. Expertise in machine learning and human omics data analysis is highly advantageous. The ideal candidate should demonstrate a high level of independence while also valuing
-
. The project will focus on using and extending deep learning-based approaches developed within the group to integrate bulk multi-omics cancer data. The Kuijjer group, established in 2018 at the University