Call for PostDoc Positions for one-year period from October 2017
in Computer Science
Faculty of Mathematics and Physics, Charles University


Research Projects:


Autonomous Robotics

Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics, Charles University solicits applications for postdoctoral research positions. The objective of the work consists in developing software technology for autonomous robots, in particular UGV/UAV (i.e., mobile robots including autonomous cars and flying drones). Relevant topics cover sensor fusion, pattern recognition, localization and mapping, path finding, goal reasoning, and activity planning, among others. The research shall be focused on artificial intelligence techniques to control the activities of the robots and to increase their autonomy. Standard hardware platforms are expected to be used.

The applicant shoud be a highly motivated scholar with PhD in computer science, preferably artificial intelligence or robotics. She/he will be collaborating on problems solved by members of our AI group (Roman Barták, Iveta Mrázová, David Obdržálek, Martin Pilát, Marta Vomlelová). Experience with real life projects is of advantage.

The project will be supervised by Prof. Roman Barták, Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics, Charles University (e-mail contact: bartak@ktiml.mff.cuni.cz).


Computer Graphics – Accurate appearance control in 3D printing and other physical fabrication processes

The proposed postdoc position is a part of a research program with the long term goal of establishing and eventually standardizing an end-to-end material appearance reproduction pipeline for 3D physical fabrication processes such as 3D printing. This involves, among other, predictive simulation of the fabrication process from the point of view of light scattering, compensation of unwanted effects of fabrication on the resulting 3D object appearance (such as blurring due to material translucency), or modeling the perception of material appearance by the Human Visual System. Furthermore, this requires development of new and accurate standardized appearance descriptors as well as appearance reproduction profiles for various fabrication devices, media and materials.

While this long-term vision necessitates a large scale research program that goes well beyond one postdoc position, we do have a specific plan tailored for the position in question, in which we directly capitalize on our accumulated expertise and research infrastructure in the area of predictive rendering. This shorter term goal is to build a predictive rendering system for various 3D printing technologies that would be capable of providing a faithful rendition of the final appearance of a planned 3D print before the actual physical fabrication. This will involve developing new fast algorithms for simulating light scattering in the 3D prints a well as measuring and modeling the scattering parameters of the printer materials. The resulting system will enable designers to preview the appearance of the planned 3D prints before the actual fabrication, saving printing material and hours of 3D printing time. Even more importantly, such a system will be the core and any follow-up research on the topic. For example, it will enable developing optimization algorithms with the goal of reaching a specific appearance, where the predictive system will serve as the predictor of the 3D prints’ appearance in each step of the optimization process.

The project will be supervised by doc. Jaroslav Křivánek (http://cgg.mff.cuni.cz/~jaroslav/), Faculty of Mathematics and Physics, Charles University.


Neural Machine Translation

The Institute of Formal and Applied Linguistics (UFAL) is seeking a candidate for a one-year post-doc position in the area of neural machine translation (NMT). The exact topic will be determined based on the candidate's interests, e.g. multi-lingual or multi-modal translation, employing linguistic resources in neural MT, MT evaluation or quality estimation, interactive MT and incremental learning.

A PhD degree in computational linguistic, artificial intelligence or a related field is required. Experience with neural MT, Linux and cluster environment (SGE), and/or general deep learning and GPU computation is a bonus.

The successful candidate will be supervised by RNDr. Ondřej Bojar, Ph.D. (Ondrej.Bojar@mff.cuni.cz).


Statistical Methods in Performance Engineering of Software Systems

The Department of Distributed and Dependable Systems is opening a postdoc position for an expert in mathematical statistics and data modeling, who would work on applying these areas in the domain of computer system performance evaluation, automated computer system performance testing, self aware and self adaptive system design and related areas.

The candidate is expected to have some experience with applying methods such as time series analysis and anomaly detection, non parametric hypothesis testing, bootstrap estimation, etc. Basic background in software engineering and computer systems is a plus. The position is open for one year, with possibility of extension.

The project will be supervised by Tomas Bures, Ph.D., Associate Professor, Department of Distributed and Dependable Systems, http://d3s.mff.cuni.cz , bures@d3s.mff.cuni.cz, Phone: (+420) 95155 4236.


These positions offer:

  • 1 year contract from October 2017 with a possible renewal in case of mutual interest
  • the salary comparable to the starting salary of an Assistant Professor at the Faculty

Interested candidates should submit:

  • CV
  • brief description of research expertise and plans (1–2 pages)
  • list of publications
  • copy of PhD thesis (or a link for downloading)
  • two letters of recommendation

Submissions should be emailed to galikova@dekanat.mff.cuni.cz not later than July 13, 2017. Shortlisted candidates may be invited for an interview.

© 2013–2017 Univerzita Karlova, Matematicko-fyzikální fakulta. Design noBrother.
Za obsah odpovídá Zaměstnanecké oddělení.