ORGANISATION/COMPANYUniversity of Tübingen
RESEARCH FIELDPhysics › Computational physics
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE01/09/2021 23:00 - Europe/Athens
LOCATIONGermany › Tübingen
TYPE OF CONTRACTTemporary
HOURS PER WEEK40
OFFER STARTING DATE01/10/2021
Using today’s computing power and software packages it has become possible to analyze large and multidimensional experimental scattering data. The process of converting these data into useful scientific information, however, can be challenging.Popular machine learning models, such as artificial neural networks, have recently shown significant advantages in terms of speed over other computational methods that are usually employed to extract the essential parameters of the investigated systems [1,2].
Within the field of soft matter physics, our group studies the fundamental structural properties, particularly the growth process, of organic thin films . In this context, we collect X-ray scattering data using highly specialized synchrotron beamlines, e.g. at the ESRF in Grenoble or at Petra III in Hamburg. Modern area detector technology allows us to record enormous amounts of complex data, however, usually data analysis remains the bottleneck for the scientific output.
 A. Greco et al., Neural network analysis of neutron and X-ray reflectivity data: Pathological cases, performance and perspectives.Mach. Learn.: Sci. Technol. 2 (2021) 045003
REQUIRED EDUCATION LEVELPhysics: PhD or equivalent
Candidates with a background in computational methods and programming with an interest in soft-matter physics
EURAXESS offer ID: 652678
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