Current open calls
- Doctoral student: We are currently evaluating candidates who applied in the that had a deadline on October 31, 2025. We are flexible with the supervision arrangements and are considering all candidates that expressed interest working with the group. The group PI counts as the required "ELLIS Fellow / Scholar / Unit Member", and hence is eligible to supervise ELLIS PhD students with any other ELLIS Member within Europe.
- Postdoc: You can apply to work with us in the with deadline February 9, 2026. We are interested in all strong applicants interested in the general topics listed below, as well as candidates that have their own research idea that aligns with our work. Joint supervision with other ELLIS PIs is possible.
- Summer interns: We are looking for 1-2 interns for summer 2026, with application deadline January 29, 2026. See the for instructions. We are primarily looking for MSc students that already have some background in statistical modelling and machine learning, but will consider also exceptional BSc students with strong mathematical background and interest in eventually pursuing a PhD in machine learning. The topic areas are listed below, and within each topic we can offer different kinds of tasks depending on the background of the candidate.
- Bayesian optimization for experimental design, with applications in food science, chemistry or ultrasonic sensing.
- Physics-informed machine learning and neural operators for approximation of physical models, and their use in solving inverse problems in ultrasonic sensing.
- Elicitation of human and LLM knowledge as probabilistic information, for instance developing an interface and application for concrete elicitation tasks.
- Human-AI collaboration in scientific research.
General interest in probabilistic modelling and machine learning for science
We will always consider exceptional students interested in doctoral studies and strong candidates for post-doctoral researcher positions. Please contact the group leader directly if interested. Some general topics of interest the group is working on right are listed below, and you are advised to relate your interests to these topics. Check also for possible open positions in artificial intelligence research in several research groups in the Helsinki area.
1. Probabilistic methods, with specific interest on efficient approximate inference (MCMC, Laplace, variational approximation) and flexible models (GPs, flows, diffusion models etc). Examples of our recent activities and work in this area:
- Research Council of Finland projects Efficient Riemannian Inference (2022-24) and Computationally Efficient Inference on Riemann Embedding Manifolds (2023-25)
- Yu et al. , AISTATS, 2024
- Luu et al. , NeurIPS, 2024
- Williams et al. , PGM, 2024
- Kusmierczyk et al. , NeurIPS, 2019
2. Collaborative AI and human modelling, with specific interest in eliciting and using tacit human knowledge. We develop theory and methods for eliciting human beliefs and knowledge as probabilistic quantities, to be used e.g. as prior information in scientific statistical models, or for explaining human behaviour. Examples of our recent activities and work:
- Research Council of Finland project Flexible priors for flexible models (2024-2028)
- Mikkola et al. , NeurIPS, 2024
- Mikkola et al. , Bayesian Analysis, 2024
- de Souza da Silva et al. , JMLR, 2023
- Hartmann et al. , UAI, 2020
3. Machine learning for science, with specific interest in virtual laboratory as domain-agnostic platform for assisting scientific research. We work e.g. on Bayesian optimization, physics-informed machine learning, neural operators, and on the general question of how to best use machine learning solutions within scientific discovery. The work can be done in context of several application areas, ranging from ultrasound physics to food science. For instance, we work on AI-assisted design of novel food production processes via use of plant and fermentation-based proteins, as part of the . Examples of our recent activities and work:
- Research Council of Finland projects Food Innovation and Diversification to Advance the Bioeconomy (2025-27) and Sustainable Industrial Ultrasonic Cleaning (2023-25), Business Finland project Virtual Laboratories for pharmaceutical R&D (2023-25), and Transcranial AI-powered ultrasound computed tomography (2026-29) funded by Jane and Aatos Erkko Foundation.
- Klami et al. , Data-Centric Engineering, 2024
- Gharib et al. , Mechanical Systems and Signal Processing, 2025
- Mikkola et al. , AISTATS, 2023