The "CIC Prize for Computational Chemistry" is awarded for outstanding master's theses and dissertations that touch on the scientific fields represented in the Computers in Chemistry (CIC) division and represent a special achievement for the further development of the field of CIC. The nominees should have completed their work at a university in a German-speaking country. Evaluation criteria include thematic relevance as well as scientific quality and presentation.

The prizes are usually awarded annually and are associated with prize money of 350 euros (master's thesis) or 750 euros (doctoral thesis), a free one-year GDCh and CIC membership if desired, as well as a certificate highlighting the merits of the award winners. From 2025, a maximum of two award winners will be honoured per call for entries.

The GDCh Division of Computers in Chemistry (CIC) invites applications for the "CIC Computational Chemistry Award" to be presented in 2026. It will be awarded for outstanding master's theses and dissertations that touch on the scientific fields represented in the division and represent a special achievement for the further development of the field of CIC. The nominees should have completed their work at a university in a German-speaking country. Evaluation criteria include thematic relevance, scientific quality and presentation. The work must have been completed between 1 January 2025 and 30 March 2026. A maximum of two award winners (1x Master's, 1x dissertation) will be honoured per call. Repeat submissions are excluded.

The jury consists of the members of the Executive Board and the associate members of the Executive Board. The Executive Board decides on the awarding of the prize after taking note of the jury's report by an absolute majority of all current members of the Executive Board. Supervisors of the proposed works are excluded from the evaluation and decision-making process.

• Letter of nomination including a brief summary of the work
• form with key data
• Master's and doctoral degree certificates, transcripts
• Dissertation/Master's thesis, if applicable, additionally in the form of publications of CIC-relevant results

Dr Jan Gerald Rittig, Rheinisch-Westfälische Technische Hochschule Aachen (RWTH), for his dissertation "Graph Machine Learning for Molecular Property Prediction and Design"

Dr Louis Bellmann, University of Hamburg, for his dissertation "Algorithmic methods for combinatorial chemical libraries"

Dr Dennis F. Dinu, University of Innsbruck, for his dissertation "Rationalising molecular vibration through matrix isolation infrared spectroscopy and vibrational configuration interaction computations"

Anne Germann, University of Düsseldorf, for her Master's thesis "Computational investigation of the mechanochemistry of 2-ladderene derivatives"

Dr Janosch Menke, University of Münster, for his dissertation "Improving Ligand-based Virtual Screening by Utilising Neural Networks to Generate Domain-specific Molecular Representations"

Dr Marwin Segler, University of Münster, for his dissertation "Computational Hypothesis Generation for Synthesis Planning, Molecular Design and Reaction Discovery"

Janine Isabel Hellmers, Kiel University, for her Master's thesis "Fragmentation Methods for Electronic Interaction Energies"

Sophia M. N. Hönig, University of Hamburg, for her Master's thesis "Convex Optimisation of Matched Molecular Series Networks and its Application to Machine Learning"

Due to the pandemic, no award ceremony took place in 2021.

Jan Blasius, University of Bonn, for his Master's thesis "Theoretical Modelling of Chiral Systems"

Dr Christoph Bannwarth, Stanford University, for his dissertation ""Development and Application of Efficient Methods for the Computation of Electronic Spectra of Large Systems"

Dr Jan Meisner, Stuttgart, for his dissertation "Theoretical Investigations of Atom Tunneling in the Interstellar Medium"

Jochen Sieg, Hamburg, for his Master's thesis "Evaluation of Benchmark Datasets for Virtual Screening with Machine Learning"

Lisa Warczinski, Bochum, for her Master's thesis "Heuristic estimation of the dynamic correlation energy: Research for the validation of a novel approach"