The research group ‘‘High Productivity Data Processing (HPDP)’’ at the Jülich Supercomputing Centre (JSC) is highly active in developing parallel and scalable machine (deep) learning algorithms for remote sensing data processing, medical research and retail sectors. By being located at JSC, HPDP can rely on state of the art High Performance Computing (HPC) technologies and innovative quantum computing systems.
What is the data science project’s research question? Can quantum computers enhance the computational performance of machine learning algorithms when solving remote sensing problems?
What data will be worked on? Open remote sensing datasets
What tasks will this project involve? Programming in Python
What makes this project interesting to work on? Access to disruptive computing technologies
What is the expected outcome? Contribution to research paper, Contribution to software development
What infrastructure, programs and tools will be used? Can they be used remotely? HPC systems and D-Wave Quantum Annealer (QA) computers. They can be used remotely.
What skills are necessary for this project? Data analytics / statistics, Scientific computation, Data mining / Machine learning, Deep learning, High-performance computing
Is the data open source? Yes
Interested candidates should be at Postdoc-level. Gabriele Cavallaro is looking for 1 visiting scientist, working on the project together with the team.