Tandartsdocent bij Digital Dentistry

Als docent begeleid je gemotiveerde studenten die zich voorbereiden op een carrière in de tandheelkunde. Met jouw ervaring als tandarts binnen de digitale tandheelkunde vergroot je hun vakinhoudelijke kennis en draag je bij aan de ontwikkeling van de volgende generatie tandartsen. Je fungeert als vraagbaak, inspirator en rolmodel.

Daarnaast ontwikkel je nieuwe didactische vaardigheden en werk je in een dynamische academische omgeving, samen met collega’s uit diverse disciplines. Hierdoor blijf je op de hoogte van de nieuwste ontwikkelingen binnen het vakgebied en breid je jouw professionele netwerk verder uit.

Jouw taken

• Bachelor en Master-studenten Tandheelkunde begeleiden/coachen met verschillende toepassingen van digitale tandheelkunde binnen het (pre) klinische onderwijs
• studenten ondersteunen bij het ontwikkelen van hun (pre) klinische competenties door middel van verschillende digitale tandheelkundige middelen, zoals VR-simulatie en CAD-CAM
• actief participeren in de voorbereiding, uitvoering en evaluatie van het digital dentistry
  onderwijs

Post-doc Computer-Aided Drug Design

The successful candidate will develop and apply Computer-Aided Drug Design (CADD) methodologies to advance drug discovery projects. Their work will focus on improving the molecular understanding of ligand-protein interactions and translating these insights into the design of novel small-molecule, drug-like compounds.

The candidate will join a well-integrated, multidisciplinary team and help guide ongoing drug synthesis and biological screening activities. The results are expected to lead to publications in high-quality scientific journals and to contribute to the specific goal of developing new medicines for Alzheimer’s disease.

Post-doc Design and synthesis of Enzyme Inhibitors

Using your experience in small-molecule organic synthesis, you will design and synthesise new heterocyclic molecules that are able to inhibit PDE enzymes. You will synthesise, isolate and characterize novel drug-like molecules. Your compounds will be screened for enzyme inhibition, enabling the development of structure-activity relationships that guide the synthesis of additional compounds.

The candidate will join a well-integrated, multidisciplinary team and work closely with colleagues who conduct Computer-Aided Drug Design (CADD) studies and biological screening. The results are expected to lead to publications in high-quality scientific journals, while also contributing to the specific goal of developing new medicines for Alzheimer’s disease.

PhD position in Social Science Genetics – VU Amsterdam & Amsterdam UMC

The Doctoral Network

ESSGN brings together eight Universities with a shared interest in social science genetics, i.e., in incorporating genetic information to improve our understanding of age-old questions in the social sciences, such as the origins of inequality, the ‘nature versus nurture’ debate, and the extent to which the interplay between environments and genes is important in shaping life chances. The consortium consists of an interdisciplinary group of academics, spanning demography, economics, epidemiology, genetics, political science, psychology, sociology, and statistics, as well as seven non-academic partners experienced in and committed to using data science to better understand inequalities in life chances. The partners include government bodies (GO Science UK), policy research institutes (RAND Europe, Netherlands Interdisciplinary Demographic Institute [NIDI]), charities (the Health Foundation), data infrastructure networks (CentERdata-ODISSEI) as well as economics consulting (Prometeia).

ESSGN creates, nurtures, and maintains a stimulating and world-class training environment in the interdisciplinary study of social-science genetics and geno-economics. Training will be provided through: i) courses in the biological foundations of genetic inheritance; ii) practical training in cutting-edge, multidisciplinary methods in social science genetics, including in state-of-the-art computational and bioinformatics methods for analysing big data and in statistical techniques for empirical research; and iii) cutting-edge academic research, to prepare the doctoral student to be a successful research scientist, but also for the professional job market in industry, technology and policy. We will coordinate and support skill development as well as monitor well-being and progress towards the PhD.

The PhD projects will jointly contribute to answering a key research question that has occupied social scientists for decades:

To what extent do inequalities in life chances arise from genetic variation, environmental factors, and their interplay, and what can we do about it?
The PhD project will go beyond the state-of-the-art by (i) using Europe’s largest and most comprehensive multi-generation databases to separate direct genetic effects from parental genetic and socio-economic factors that shape the rearing environment; and (ii) by exploiting the large toolbox of causal inference methods used in econometrics and statistics to estimate how environmental contexts causally protect individuals with genetic risk.

We will incorporate genetic information into the social sciences to explore how genetic and environmental characteristics jointly shape inequalities in life chances by (1) analysing to what extent genetic (‘nature’) and environmental (‘nurture’) factors contribute to inequality of opportunity and intergenerational mobility, and (2) establishing how nature and nurture jointly shape inequalities in life chances.

Three fully funded PhD positions in Competition Law and AI

Every EU competition agency, and most agencies worldwide, now relies on AI and other computational tools to enforce competition law. The legal framework has not kept pace. ATLANTIS, a five-year project funded by an ERC Consolidator Grant (grant agreement 101228709), builds that framework.

I am Thibault Schrepel, Associate Professor of Law at Vrije Universiteit Amsterdam, and I am hiring three PhD candidates to join the ATLANTIS team. Two positions are legal-track. One is a cross-project computational position. The positions begin on 1 December 2026, last four years, and are based at the VU Amsterdam Faculty of Law. All three candidates will obtain a doctorate.

The three PhD positions
Together, we will build the legal regime for computational antitrust.

The team has one legal-track PhD candidate dedicated to Project A, one legal-track PhD candidate dedicated to Project B, and one (more) computational-track PhD candidate working across both projects. The computational-track candidate will provide the empirical and technical scaffolding needed by the two legal-track candidates. The legal-track candidates will provide the competition law expertise that keeps the technical work tied to live antitrust problems. All three candidates will obtain a doctorate.

A postdoctoral researcher with expertise in institutional economics will join the team about a year after the PhDs start.

Project A: making computational antitrust accurate (one PhD position)
This legal-track PhD will work on the legal framework for data access by competition agencies. The core question is whether Regulation 1/2003 and Directive (EU) 2019/1 need to be updated so that the European Commission and national competition agencies can collect the data their computational tools require while preserving fundamental rights. The project will address data protection, business secrecy, the right to remain silent, and proportionality.

Project B: making computational antitrust fair (one PhD position)
This legal-track PhD will work on the legal regime governing the use of AI by competition agencies. The core question is how to mitigate bias and ensure procedural fairness when agencies rely on AI tools. The project will address transparency, explainability, AI-generated evidence, and standards of proof.

Cross-project computational position (one PhD position)
This PhD will work across Projects A and B and provide the technical backbone of the team. On Project A, the focus will be on data: documenting what data agencies collect, through which channels, in which formats, and where computational bottlenecks arise. On Project B, the focus will be on AI methods: auditing bias in publicly documented agency AI systems and prototyping explainability techniques on representative cases. Although more computational in nature, this position will lead to publications in law venues.

What you will be doing
ATLANTIS will be run as a tight team, not as three PhDs working in parallel silos. We will work together daily (being on campus several days a week will be expected). Drafts circulate inside the team before they go to the international advisory board. Papers are co-authored. You will publish from year one.

Your time will be divided between writing peer-reviewed articles, conducting empirical work with competition agencies, co-organizing ATLANTIS events, and presenting your work to the international advisory board and conferences. Each PhD co-authors several articles with me over four years. At the end of the project, the team co-edits a volume that consolidates the research. You will end up with publications, a book chapter or more, policy briefs, and a body of empirical work you helped build.

You will have direct access to the network of the Stanford Computational Antitrust project, which gathers over 80 antitrust agencies and 50 academics worldwide. It means real interviews, real data-sharing arrangements, real introductions, and the option of visiting agencies that have committed to the project. The agencies involved span multiple jurisdictions including Australia, Brazil, Canada, France, Germany, Japan, the Netherlands, Singapore, South Africa, the UK, and the United States.

You will spend research stays at the institutions of the co-supervisors and the international advisory board. These include leading scholars from Oxford, MIT, Stanford, Harvard, and other top institutions.

You will help organize three annual workshops and an international conference at the end of the project. You will not be a passive attendee. You will shape the programs, invite speakers, present your own work.

You will also teach a small share of your time, capped at 20% over four years under the CAO of Dutch universities. Teaching is supervised and matched to your interests. It will focus on competition law or law & tech issues.