Postdoctoral position in computational, evolutionary, mathematical oncology

Date limit
Universidad Autónoma de Madrid (UAM)


The Ramon Díaz-Uriarte's group is looking for a postdoc for a 12 month position (possibly 14 months) to join the group at the Biochemistry department, Medicine Faculty, Universidad Autonoma de Madrid (Madrid, Spain).

Gross monthly income of aprox. 2200 euros.
Starting date: as soon as possible (though call will remain open for several months until candidates are found).
The project is funded by the Spanish AEI/MCIN.

Interested candidates please write Ramon Diaz-Uriarte ( with subject POSTDOC-111256RB-3. Include a letter of interest and CV.

Summary of work to be developed

  1. Programming and optimization of simulation software in scientific environments, using the languages R, C++, and Julia (and, as needed, other specific languages or libraries).
  2. Programming and development of tumor progression models, using R, C++, and Julia languages (and, as needed, other specific languages or libraries),
  3. Management and statistical analysis of massive simulations of evolutionary processes in cancer and their processing with existing methods, as well as with methods newly developed by our group.
  4. Dissemination of results: writing of scientific articles, attending to conferences.

Merits to be valued

  1. Publications in one or more of the following areas: computational biology, evolutionary biology, statistics and probability, computer science applications, biophysics, applied mathematics, modeling and simulation.
  2. Research experience in some of the following areas: computational biology and mathematical oncology; evolutionary biology and population genetics (theoretical); stochastic simulation; development of probabilistic models (preferably in evolutionary biology and mathematical oncology) and Bayesian statistics; causal inference.
  3. Experience with one or more of R, C++, and Julia programming languages. Also valued: experience with Stan, Python, C, Clojure, Javascript, probabilistic programming and deep learning libraries, as well as experience with high-performance computing.