Description

Leader of the group Life Sciences and Health: Leen Stougie.

The CWI Life Sciences and Health (LSH) group is a group of computer scientists and mathematicians whose research focus is on the analysis and design of models and algorithms as well as their direct application to important challenges in the LSH domain.

On the application side, our present team of researchers has expertise in, e.g., computational genomics, medical informatics, computational phylogenetics, and biological network analysis. On the methodological side, we come from different backgrounds, e.g., computational intelligence, computational data science, and operations research. Methodologically, we develop new theories, models, algorithms and decision support tools, for problems that arise mostly in collaboration with experimental biologists and medical experts. We actively collaborate in projects with academic hospitals, biological and biochemical research institutes, and industry. Click here for more information about our group structure.

The LSH group participates in the INRIA International team ERABLE.

Seminars: The LSH group organizes a biweekly seminar.

Watch our group video to get a glimpse of our activities.

 

 

Vacancies

PhD students on innovating model-based evolutionary algorithms from algorithmic foundations to medical applications

Centrum Wiskunde & Informatica (CWI, the Dutch national research institute for mathematics and computer science) located in Amsterdam, and the Leiden University Medical Centre (LUMC) together have 10 vacancies for fully funded PhD students, on innovating model-based evolutionary algorithms from algorithmic foundations to medical applications.

News

Members

Associated Members

Publications

Software

Current projects with external funding

  • Improving Childhood Cancer Care when Parents Cannot be There - Reducing Medical Traumatic Stress in Childhood Cancer Patients by Bonding with a Robot Companion ()
  • Enhancing protein-drug binding prediction
  • ICT based Innovations in the Battle against Cancer – Next - Generation Patient -Tailored Brachytherapy Cancer Treatment Planning
  • Statistical Models for Structural Genetic Variants in the Genome of the Netherlands
  • Algorithms for PAngenome Computational Analysis (ALPACA)
  • Fast, accurate, and insightful brachytherapy treatment planning for cervical cancer through artificial intelligence (Brachytherapy treatment)
  • Evolutionary eXplainable Artificial Medical INtelligence Engine (EXAMINE)
  • Fusible Evolutionary Deep Neural Network Mixture Learning from Distributed Data for Robust Medical Image Analysis (FEDMix)
  • Multi-Objective Deformable Image Registration (MODIR) – An Innovative Synergy of Multi-Objective Optimization, Machine Learning, and Biomechanical Modeling for the Registration of Medical Images with (MODIR)
  • Networks
  • Optimization for and with Machine Learning (OPTIMAL)
  • Pan-genome Graph Algorithms and Data Integration (PANGAIA)
  • Transparent, Reliable and Unbiased Smart Tool for AI (TRUST-AI)

Related partners

  • AMC Medical Research
  • CNRS
  • Elekta Limited
  • European Molecular Biology Laboratory
  • INRIA
  • Nucletron Operations BV
  • Universita di Pisa
  • Xomnia
  • Academisch Medisch Centrum
  • Biomedical Imaging Group Rotterdam
  • Erasmus Universiteit Rotterdam
  • Geneton S.R.O.
  • Heinrich-Heine-Universitaet Dusseldorf
  • Illumina Cambridge
  • Institut Pasteur
  • Leids Universitair Mediach Centrum
  • Technische Universiteit Delft
  • Univerzita Komenskeho V Bratislave
  • Universiteit Leiden
  • Universitaet Bielefeld
  • Universita' Degli Studi di Milano-Bicocca
  • Universiteit van Tilburg