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”.

 

More details and application link can be found at https://www.h-its.org/hits-job/phd-position-m-f-d-in-computational-chemistry-and-machine-learning/. Closing date for this position is 1st of March 2023. The starting date is negotiable.
 
This 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. High-level quantum-chemical simulations will also be employed 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.

​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.

Best regards,

Anya