For any questions, do not hesitate to ask:
Dr. Nico Hoffmann Tel.: +49 351 260 3668
Place of work:
30 April 2021
The HZDR is committed to equal opportunity employment and we strongly encourage applications from qualified female candidates. We also carefully consider all applications from job candidates with severe disabilities.
Bautzner Landstraße 400
PostDoc (f/m/d) Inverse Imaging Problems
As member of the Helmholtz Association of German Research Centers, the HZDR employs about 1,400 people. The Center's focus is on interdisciplinary research in the areas energy, health and matter.
The Helmholtz AI Young Investigators Group “AI in Future Photon Science” invites applications for a
PostDoc (f/m/d) Inverse Imaging Problems.
The Helmholtz AI YIG contributes to the research on novel Laser-Plasma particle accelerators of HZDR’s Institute of Radiation Physics by accelerating numerical simulations as well as reconstructing experimental diagnostics using numerical methods and recent advances in machine learning. The comprehension of fundamental physical principles in Laser-Plasma acceleration requires sophisticated mathematical and data-driven methods for fast reconstruction of diagnostics such as Small-angle X-ray scattering, Ptychography, Coherent Transition Radiation. The focus of your position will be the research of advanced reconstruction methods for ill-posed inverse imaging problems by integrating invertible neural networks into gradient-based optimisation techniques to approach the phase problem from a mathematical as well as machine learning perspective!
You will be working in an interdisciplinary team of machine learning researchers, data scientists as well as experimental- & theoretical physicists who are very experienced in solving inverse problems (e.g. phase problem), surrogate modelling and PDE learning. You will also be part of our local Helmholtz AI initiative offering knowledge transfer & stimulating discussions with a growing number of machine learning enthusiasts. Our HZDR-wide "ML clinic" as well as social events (hackathons, paper reading groups, etc.) are certainly open to you, too.
The position will be available from the earliest starting date. The employment contract is limited to two years.
- designing fast & robust ML-assisted algorithms for solving ill-posed inverse imaging problems
- identification of imaging techniques that enable and/or improve reconstruction of X-ray scattering
- proactive collaboration with experimentalists to translate knowledge into experimental planning
- publishing papers in high-quality refereed conferences and journals in Physics, Mathematics and Machine Learning
- presentation of research results at scientific meetings
- contribution to preparation of new grant proposals/studies
- actively collaborating with industry, academia, government labs and applications developers in a variety of venues
- PhD in Mathematics, Physics, Computer Science or a closely related discipline
- strong mathematical background (e.g. linear algebra, non-convex optimization)
- publication record in computational imaging, inverse problems, machine learning
- good programming skills in Python
- preferably: experience in solving ill-posed inverse problems (e.g. phase retrieval)
- preferably: proven knowledge in analysis/reconstruction of X-ray imaging modalities (SAXS, CDI, Ptychography, etc.)
- topics of interest include: X-ray imaging, Phase Contrast Imaging, Machine Learning, Image Analysis, Deep Generative Models, ill-posed inverse problems
- A vibrant research community in an open, diverse, and international work environment
- Scientific excellence and extensive professional networking opportunities
- The employment contract is limited to two years with the possibility of longer-term prospects
- Salary and social benefits in conformity with the provisions of the Collective Agreement TVöD-Bund
- 30 Vacation Days per year
- Company pension scheme (VBL)
- A good work/life balance for which we offer assistance in the form of:
possibility to work part-time
flexible working hours
in-house health management
Kindly submit your completed application (including cover letter, CV, diplomas/transcripts, etc.) only via our Online-application-system.