PhD in modelling of heterogeneous medical data for clinical impact

Region Hovedstaden

Ph.d. & forskning

The chronic lymphocytic leukemia (CLL) lab at Rigshospitalet, invite applications for an appointment as PhD student (health sciences, Copenhagen University) in modelling of heterogeneous medical data for clinical impact. The position is available from February, 2020 or according to mutual agreement.

Responsibilities and tasks
Machine learning on medical data has several challenges that need to be overcome for clinical implementation. This includes making predictions with low sample sizes, high dimensions and missing data. In this PhD you will be at the forefront of defining methodologies for handling missing data, combining multiple data-sources and providing trustable predictions for the clinic. You will carry out collaborative work with high profile partners at Technical University of Denmark (DTU), Institute Pasteur and for addressing key research questions related to chronic lymphocytic leukemia (CLL) and other lymphoproliferative malignancies. The research will focus on providing clinical value using ML strategies and includes:

  • Novel machine learning strategies for combining multidimensional clinical data from various sources such as flow cytometry, next generation DNA sequencing, gene expression & functional assays, baseline clinical, and para-clinical data.
  • Novel machine learning methods for cleaning and organizing clinical data with least bias.
  • Effective handling of missing data and low sample sizes.
  • Methods for interpretation of trained machine learning models with clinical viability in mind.
  • Publishing on High-Impact factor journals (NEJM, Blood, Nature Comm.)
  • Effective communication with medical doctors on modelling strategy choices and results.

Research environment
We offer a challenging PhD in an international environment. We value knowledge sharing and multi-disciplinarity. Hence, you are expected to cooperate and be eager to build relations with colleagues within the department and with collaboration partners. Through our collaboration with PERSIMUNE, you will be uniquely positioned to access rich and carefully curated datasets that are unattainable anywhere else in the world. Additionally, through our collaboration with DTU, you will have access to the high-performance computing (HPC) clusters for computational requirements. Our research group has the setup needed for fast testing in clinical trials through international collaborations (PreVent-ACaLL trial, NCT03868722), therefore there is ample opportunity for your work as a modeller to have direct clinical impact. Our current research-group includes 5 scientific researchers (4 PhDs and 1 Post-Doc), 3 laboratory technicians, 20 clinical trial unit employees at the Department of Hematology, and 50+ data cleaning and structural IT technicians at the PERSIMUNE data lake. We strive for academic excellence, collegial respect and freedom tempered by responsibility. We also believe in each individual’s patterns of productivity. We welcome flexible time and location of working hours, as long as the quota for the full-time work week is reached.


  • At least Bachelor’s degree in computational, mathematical, physical or life sciences.
  • Researchexperience with machine learning methodologies.
  • A broad tool set of several supervised learning strategies, including non-deep learning-based methods, feature selection and unsupervised learning.
  • Ability to explain motivations, methodologies and results to audiences of various technical backgrounds.
  • Programming experience.
  • Ability to work both independently and as a team-player.
  • Mastering of the English language with proficiency.
  • Domain knowledge within modelling of medical data is not required. The ability to transfer your knowledge to medical problems is however expected.
  • Creative mindset and curious mind.

Salary and terms of employment
The appointment will be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed with the relevant union.

Workplace and period of employment

  • Rigshospitalet, Copenhagen.
  • The period of employment is 1-year (with extension to 3 years depending on funding).

Further information on our group may be obtained from Please contact Dr. Rudi Agius ( and Dr. Carsten Utoft Niemann on ( for further details regarding this PhD position.

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