06 Postdoctoral Fellowship at Groningen, Netherlands

Personalised medicine requires the correct selection of medications to appropriately address individual patient characteristics. In the case of non-small cell lung cancer (NSCLC), novel mutations often arise as a result of target therapy (kinase inhibitors), resulting in a lack of clarity for the most impactful treatment options. A molecular understanding of the tumour response to treatment can then bring this much-needed clarity, and implementing this understanding into computational tools can provide the potential for rapid clinical response to patients.

The DELPHI project, a collaboration between UMCG, UG, Health-Ecore and Protyton, aims to advance lung cancer treatment using molecular modeling and computational analysis for personalised care. DELPHI seeks to provide targeted interventions for improved patient outcomes. Aligned with RIS3 aims, it strengthens the Northern innovation ecosystem.

The specific role of the postdoctoral researcher working in this position will be to provide in vitro biochemical, biophysical and structural data from novel mutants of the EGFR kinase domain to drive and validate algorithmic development.

We are looking for PD candidate for a joint project between the groups of Prof. Ben Feringa and AkzoNobel, within the framework of the Advanced Research Center Chemical Building Blocks Consortium (ARC-CBBC – https://arc-cbbc.nl/). As an industrial-academic consortium, the chemical building blocks consortium brings together leading laboratories in chemistry and materials sciences with research-intensive and innovation-oriented industrial partners. As core expertise, the consortium specializes in developing new chemical building blocks that, when applied on industrial scale and with industry-leading technology, have the potential to revolutionize consumer-goods and products. ARC CBBC has a strong focus on sustainability, enabling transitions towards a circular and more balanced economy with regard to energy, feedstock, and materials.

Recently, in the context of the development of sustainable alternatives for acrylates widely used in coating industry, we achieved in our lab the efficient synthesis of hydroxybutenolide through the photooxidation of furfural, a biomass-derived precursor by using continuous flow reactor (DOI: 10.1039/D2RE00310D). We further demonstrated the potential of butenolide derivatives for polymer coatings (DOI: 10.1126/sciadv.abe0026, DOI: 10.1039/D2GC03657F). The focus of this project is the study of emulsion polymerization of biobased butenolides to develop coatings with application-targeted properties. This includes development of polymerization methods, formulation of coatings and their testing.

In additional to the academic advisor, the PD candidate will be in close collaboration with the industrial partner to this project, AkzoNobel. The research will take place at the University of Groningen, but if required, the researcher may be able to use AkzoNobel equipment and will be aided by the industrial partners’ specific expertise. As such, this research provides a unique opportunity to get introduced to industrial Research & Development, while working in an academic environment.

A postdoc position in computational social choice for AI Safety is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence of the University of Groningen in The Netherlands.

The position is available within the research project “Aggregating Safety Prefer-ences for AI Systems: A Social Choice Approach.” The project aims to develop formal methods for eliciting and aggregating safety specifications and risk thresh-olds for AI systems, with a particular focus on mechanisms that provide axiomatic guarantees, are algorithmically tractable, and show good performance in computa-tional experiments. The project’s research outcomes are expected to contribute to the design of safeguarded AI systems that reflect diverse stakeholder prefer-ences. This project is funded by the Advanced Research + Invention Agency (ARIA) as part of their Safeguarded AI program that aims to develop the safety standards needed for transformational AI. The successful candidate would become an ARIA R&D creator.

We are seeking a motivated and skilled Postdoctoral Researcher to join a collaborative project between Dr. Xiaohua Li at the University of Groningen and our industrial partner IonIQs. The focus of this project is the development of advanced electrochemical purification methods to recover lithium from industrial wastewater.

In this project, the postdoctoral researcher will focus on the fundamental understanding and process optimization of an electrochemical cell system incorporating redox-flow electrodes and ion-selective membranes for Lithium purification. The goal is to selectively remove impurities—such as sodium (Na), calcium (Ca), and magnesium (Mg)—from lithium-rich wastewater streams, thereby enabling the recovery of high-purity, battery-grade lithium.

The project will be supervised by academic PIs at the University of Groningen and the industrial partner, ensuring strong mentorship and research guidance. The research will be conducted mainly at the IonIQs laboratory on the Zernike Campus of the University of Groningen, offering a unique opportunity to work at the interface of academic research and industrial innovation.
This project offers an excellent opportunity to contribute to a sustainable and circular lithium economy by integrating materials science, electrochemistry, and membrane technology.

Topic of research: Fundamentals in the growth behavior of ultrahigh temperature TaC coatings for producing epitaxial SiC semiconductor

Reliable protective coatings are exigently demanded to coat graphite crucibles and susceptors for bulk SiC crystal and epitaxial SiC film growth processes for supplying wide bandgap materials in the fast growing market of semiconductor power devices. Presently thick TaC coating on graphite is being developed to catch up the demand. However, this crucial development is currently hampered by the high tendency of dense micro-cracks and delamination of TaC coating from the graphite substrate, which are mainly caused by the large thermal expansion mismatch between the coating and graphite substrate during chemical vapor deposition and during service by the thermal cycles from room temperature to the service temperatures (up to 2600 °C).
This research project aims understanding the fundamentals in the growth behavior of ultrahigh temperature TaC coating on graphite with chemical vapor deposition and eventually developing a crack-free and crack-tolerant TaC coating for the semiconductor industry.