Postdoc in Machine Learning Methods for Single-Cell Data
KTH Royal Institute of Technology,
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as in architecture, industrial management, urban planning, history and philosophy.
Your work will take place at the department of Computational Science and Technology - CST. For more information go to, https://www.kth.se/en/csc/forskning/cst
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.
Trade union representatives
You will find contact information to trade union representatives at KTH:s webbpage.
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:
1 Curriculum vitae.
2 Transcripts from University/ University College.
3 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.
We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.
Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.
|Type of employment||Temporary position longer than 6 months|
|Contract type||Full time|
|First day of employment||Så snart som möjligt|
|Number of positions||1|
|Last application date||15.May.2017 11:59 PM CET|