Fully funded PhD positions: machine-learning compiler framework
The Computer Systems Lab at Ghent University has open positions in the domain of compiler and software development technology. In the context of a research project on the development of more productive programming environments for smart cameras and other distributed and parallel embedded systems, we are looking for PhD students that want to design and develop a globally optimizing and parallelizing software design-space exploration framework based on machine learning. This compiler framework and the corresponding software libraries should enable machine-vision programmers to write high-level implementations in, e.g., Python, of their machine vision algorithms, for which the framework then explores possible algorithmic instantiations and optimizes them for specific target processors, including coarse-grained reconfigurable processors such as ADRES, and GPUs. In short, this project wants to design a programming tool box that delivers programmer productivity and performance portability.
In this project, the individual PhD students can focus on different aspects of this framework, according to their own interests and expertise. Experience in and passion for compiler technology, Python (or equivalent) programming, parallel programming, programming design patterns and machine learning are beneficial. For this research, the PhD students will mainly collaborate with computer vision researchers from UGhent's Image Processing and Interpretation research group, as well as with machine learning and backend compiler and computer architecture researchers from UGhent's Computer Systems Lab and from IMEC.
A PhD position requires a Master of Science in Computer Science, Computer Engineering, or equivalent in a field which is relevant for the topic of the PhD thesis. The positions are initially for four years, extensible to five years, and include departmental duties at a level of at most 15% (typically teaching assistant for one course during one semester).
Applications should include a description of research interests and past experience, a CV, copies of exams, degrees and grades, a copy of Master thesis (or a draft thereof), relevant publications, and other relevant documents. Candidates are encouraged to provide letter(s) of recommendation and contact information to reference persons, as well as earliest feasible starting date of employment. These applications are to be sent to firstname.lastname@example.org.
For further questions, please contact prof. Bjorn De Sutter at the same mail address or at +32 9 264 33 67.