Sort by
Refine Your Search
-
– from the modeling of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference
-
the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
-
of the German Armed Forces Munich), the DLR (German Aerospace Center) with its Oberpfaffenhofen institutes, and the BHL, the Bauhaus Luftfahrt. This pooling of research, graduate programmes and teaching merges
-
. Beyond the financial support, the programme offers non-material support such as yearly PhD scholar forum and workshops, which aim at fostering personal growth, promoting interdisciplinary qualification as
-
the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
-
), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine
-
missions. Prior experience with methods of statistical inference using simulations or anomaly searches with machine-learning approaches is desirable.
-
. The PhD project will be in collaboration with the Leigh lab at Senckenberg, and part of a team of four complementary PhD students in FynFUN. It will be embedded in the TERRA Cluster of Excellence and
-
Description The Institute of Biochemistry of the Medical Faculty at Kiel University (CAU) is seeking to appoint a PhD student (m/f/d) to join the research group of Dr. Matthias Voss as soon as
-
expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as well as the absolute