Time Span as soon as possible for 4 years Application Deadline 31 Mar 2023 Financing yes Type of Position
Field of Research
Subjects chemistry, physics, materials science, or a related discipline Description The Computational Carbon Chemistry (CCC) group at the Heidelberg Institute for Theoretical Studies (HITS gGmbH) is looking to fill a
PhD position (m/f/d) in computational chemistry and machine learning
to work on the ERC Starting Grant “PATTERNCHEM: Shape and Topology as Descriptors of Chemical and Physical Properties in Functional Organic Materials”.
Your interdisciplinary research project will involve developing and implementing novel machine learning representations and fingerprints of shapes and topologies for diverse functional organic materials, including graphene derivatives, covalent organic frameworks, and hyperbranched polymers. You will also use high-level quantum-chemical simulations to design custom descriptors of the non-covalent interactions between materials and small molecules. The ultimate goal of PATTERNCHEM is to build an all-encompassing, adaptable framework for modelling interactions of multifaceted functional organic materials with their molecular targets, filling the missing links with newly devised structural fingerprints and energetic descriptors.
What qualifies you for this job
Successful candidates should have a Master's degree (or be close to completion) in chemistry, physics, materials science, or a related discipline, and, preferably, an experience in theoretical chemistry, numerical simulations, data science, and coding.
See full announcement at: https: // www. h-its.org/de/hits-job/phd-position-m-f-d-in-computational- chemistry-and-machine-learning/
Language of Dissertation
More Information https: // www. h-its.org/de/hits-job/phd-position-m-f-d- in-computational-chemistry-and-machine-learning/