The project is concerned method development in machine learning and probabilistic modeling as well as application of the developed methods. The goal is to facilitate investigations of developmental, temporal, and spatial aspect through analysis of cutting edge biological data that has single cell resolution, in some cases also carrying spatial information. Methodologically, this project will be focused on advanced methods for computational inference such as Expectation Maximization, Sequential Markov Chain, Variational Inference, Markov Chain Monte Carlo (MCMC), and Particle MCMC methods, as well as obtaining efficient implementation of such methods by taking advantage of modern computational technology. We will also actively collaborate, with groups developing new experimental methods as well as generating medically relevant data, in more applied projects.
This is a two-year time-limited position. The starting date is open for discussion, though ideally we would like the successful candidate to start as soon as possible.
Applicants should have a PhD degree received within the last three years. If the applicant has an older PhD, they will be employed to a research position.
You need a very strong computational background, preferably in algorithm design, machine learning, and HPC. Very good programming skills is a requirement. A good understanding of Biology is a clear merit, but a strong motivation to understand and contribute to biology is a prerequisite.
Log into KTH's recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad.
Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).
Application shall include the following documents:
- Curriculum vitae.
- Transcripts from University/ University College.
- Brief description of why the applicant wishes to become a doctoral student.
Please observe that all material needs to be in English, apart from the official document.
Contact Jens Lagergren, Professor, +46 73-9682322