The advent of modern machine learning (ML) methodology is accelerating scientific progress by streamlining research across disciplines. In chemistry, it enables the modeling of complex structure-function relationships with unprecedented accuracy. Additionally, deep generative models allow for the generation of structures with desired function, thus enabling the design of novel molecules and materials.

Peptide-based materials provide attractive alternatives to materials derived from petrochemicals. By tuning the peptide sequence and modifications, material properties can be finely tuned. Their behavior at surfaces and interfaces are among the most fundamental, but also most important properties of small peptides. Control over these materials can enable a new generation of biodegradable materials, surfactants and coatings. However, how peptide sequence and modification affect the physicochemical properties and material performance remains unclear, let alone inverse design of these molecules.

The goal of this project is to develop ML models for: 1) predicting properties of oligopeptide materials based on peptide sequence and end-group functionalization; 2) guiding experimental structure optimization workflows to minimize the number of experiments to achieve desired properties; 3) generating new peptide sequences with desired target properties.
This position will be part of the 10 (https://bigchemistry.nl/), which combines laboratory automation with artificial intelligence. By building an autonomous ‘RobotLab’, large numbers of experiments can be carried out, yielding large datasets on properties of molecular systems. With this data, ML models are trained to predict the properties of molecular systems such as solubility, phase separation, critical micelle concentration, smell, toxicity, and reaction rates.

Organization

Founded in 1614, the University of Groningen enjoys an excellent international reputation as a dynamic and innovative institution of higher education offering high-quality teaching and research. Flexible study programs and academic career opportunities in a wide variety of disciplines encourage the 31,000 students and researchers alike to develop their own individual talents. As one of the best research institutions in Europe, the University of Groningen has joined forces with other top universities and networks worldwide to become a truly global center of knowledge, situated in the vibrant city of Groningen in the north of The Netherlands.

The successful candidate for this position will have the following qualifications/qualities:
- A PhD degree in either machine learning or computational molecular sciences.
- Advanced knowledge in molecular machine learning.
- Advanced knowledge in computational chemistry.
- Advanced programming skills and experience with scientific software development.
- Excellent knowledge of written and spoken English.
- Excellent communication skills, especially for collaborating with others.
- Enthusiasm and initiative to perform creative research in an interdisciplinary setting.

Fixed-term contract: 18 months.

The University of Groningen offers, in accordance with the Collective Labour Agreement for Dutch Universities:
- A salary of € 3877.- gross per month (scale 10, step 4) in the first year to a maximum of € 4185, - gross per month (scale 10, step 6) (salary scale Dutch Universities), based on a full-time position (1.0 FTE), depending on relevant work experience after attaining a PhD.
- A gross holiday allowance of 8%.
- A gross 8.3% year-end bonus.
- A position for a period of 1.5 years.

Rober Pollice
r.pollice@rug.nl