Postdoctoral Researcher in Machine Learning and Quantum Computing for Health Data Science

23 hours ago


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

Københavns Universitet (KU) is a leading research-intensive university with a strong focus on interdisciplinary collaboration. Our Department of Computer Science is renowned for its cutting-edge research in artificial intelligence, quantum computing, and health data science.

Job Description

We are seeking a highly skilled Postdoctoral Researcher to join our team in the field of machine learning and quantum computing for health data science. As a member of our group, you will have the opportunity to work on exciting projects that combine theoretical and experimental approaches to tackle complex problems in medical data analysis.

Responsibilities:
  • Conduct research on the development and application of deep generative models and quantum computing techniques for biomedical data analysis.
  • Collaborate with our team of researchers and experimental collaborators to design and implement novel algorithms and methods for protein-ligand binding and other biological or medical applications.
Requirements

To be successful in this role, you should have a PhD in bioinformatics, computational biology, or a related field, and several years of postdoctoral experience in machine learning and generative models. You should also have excellent programming skills in Python and PyTorch, as well as a strong understanding of mathematical and statistical concepts.

What We Offer

We offer a competitive salary of approximately DKK 530,000 - 590,000 per year, depending on your level of experience. Additionally, you will have access to a range of benefits, including flexible working hours, opportunities for professional development, and a dynamic and supportive work environment.

How to Apply

To apply for this position, please submit your application electronically through our website. Your application should include your curriculum vitae, diplomas, complete publication list, and separate reprints of three particularly relevant papers. The deadline for applications is September 17, 2024.



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