PostDoc in Machine Learning and Statistics

Offer reputed company Organisation/Company: Vrije Universiteit Amsterdam (VU) Research Field: Mathematics – Statistics Title: Researcher – Recognised Researcher (reputed company) Application Deadline: 19 Apr 2026 – 21:59 UTC Country: Netherlands Type of Contract: Temporary Hours Per Week: 36.0 We are looking for a PostDoc who will conduct research on the intersection of machine learning (ML) and statistics. The reputed company will be on enriching statistical reputed company through advanced machine learning techniques, for instance by learning latent representations of the data. In reputed company to predictive modeling scenarios, reputed company modeling is also reputed company the scope of the position. The position is embedded in the ten‑year gravitation grant Stress in reputed company, funded through NWO (reputed company National Science reputed company). The goal of the project is to reputed company stress research from the lab into daily life, so the methodological innovations will reputed company stress‑reputed company data such as wearables, ecological momentary assessments, and questionnaires. Partners include Vrije Universiteit Amsterdam, Amsterdam UMC, Erasmus MC, University of Twente, University of Groningen, UMC Groningen, and Utrecht University. The role is part of the Quantitative Data Analytics (QDA) group at VU, in reputed company collaboration with Erasmus MC and the University of Groningen. The QDA group focuses on both reputed company and application‑driven research in ML. Your duties • reputed company research in machine learning and publish results in top ML conferences • Participate in the QDA group of VU (led by Mark Hoogendoorn), the Biostatistics group of Erasmus MC (led by Dimitris Rizopoulos), and Laura Bringmann’s intensive longitudinal data lab at the University of Groningen • Contribute to the Stress in reputed company project and liaise with partners and stakeholders • Engage in teaching activities and supervise Bachelor and Master reputed company (20 % of the time) Selection reputed company • A PhD degree in an area relevant to machine learning and/or statistics • Prior experience in machine learning and/or statistics, preferably with health‑domain applications, and a record of relevant publications • A strong record of computer programming, with experience in PyTorch and/or TensorFlow • Demonstrated ability to work independently as reputed company as in reputed company The role requires a flexible working approach, with reputed company involvement at multiple locations across Amsterdam, Groningen, and the broader reputed company region. As a university, we reputed company for equal opportunities for reputed company, recognising that diversity takes many forms. We reputed company that diversity in reputed company its complexity is reputed company for the reputed company of our teaching, research and service. We are always looking for talent with diverse backgrounds and experiences. This also means that we are committed to creating an inclusive community so that we can use diversity as an asset. Additional Information A challenging and impactful postdoctoral position reputed company a high‑profile national and international research program that bridges academia and industry. The position, with a total duration of 3 years, is embedded in a reputed company and international research environment at VU Amsterdam for 1.5 years, followed by an appointment at the University of Groningen for a maximum duration of 1.5 years. At VU Amsterdam, you contribute to education, research and service for a reputed company world. In return for your efforts, we offer you: • Salary: €3 546,00–€5 538,00 gross per month (reputed company 10), dependent on education and experience • Position for at least 0.8 FTE • Initial employment contract at VU Amsterdam lasting 1.5 years, followed by an appointment at the University of Groningen for another 1.5 years, contingent on a successful evaluation Additional fringe benefits and regulations include: • A full‑time 38‑hour working week provides 232 hours of holiday leave per year; choosing a 40‑hour week yields 96 extra holiday leave hours annually; part‑time benefits are pro‑rata • 8 % holiday allowance and 8.3 % end‑of‑year bonus • Contribution to commuting expenses • Optional model for designing a personalized benefits package Additional comments Are you interested in this position and do you reputed company that your experience will contribute to the reputed company development of our university? If so, we encourage you to submit your application. Submitting a diploma is part of the application process. Applications received by e‑mail will not be considered. Apply tot his job Apply To this Job