Senior Machine Learning Researcher for Health Data Science

3 days ago


Copenhagen, Copenhagen, Denmark Københavns Universitet (KU) Full time

About Us

Københavns Universitet (KU) is a leading research university in the field of computer science. Our department is committed to advancing knowledge in this area through innovative research and education.

We are seeking a highly motivated postdoctoral researcher to join our team in the Department of Computer Science at KU. The successful candidate will be part of a dynamic research group focused on developing deep generative models, quantum computing, and applications to medical data.

The primary responsibility of the position is to conduct research on machine learning and quantum computing applied to protein-ligand binding and other biological or medical applications. This involves collaborating with theoretical and experimental collaborators in math and physics to develop new methods and techniques.

The ideal candidate will have a PhD and MSc in bioinformatics, computational biology, or a similar field, as well as solid experience in machine learning and generative models. They should also be an expert in molecular modeling and dynamics of proteins, with several years of programming experience in Python and PyTorch.

Job Description

  • Conduct research on machine learning and quantum computing applied to protein-ligand binding and other biological or medical applications.
  • Collaborate with theoretical and experimental collaborators in math and physics to develop new methods and techniques.
  • Develop deep generative neural networks for biomedical applications.

Required Skills and Qualifications

  • PhD and MSc in bioinformatics, computational biology, or a similar field.
  • Solid experience in machine learning and generative models.
  • Expertise in molecular modeling and dynamics of proteins.
  • Several years of programming experience in Python and PyTorch.

Benefits

  • A competitive salary and benefits package.
  • The opportunity to work with a dynamic research group and collaborate with leading experts in the field.
  • A chance to contribute to cutting-edge research and publication opportunities.


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