The Finnish Center for Artificial intelligence FCAI is searching for early career scientists to join our research team working towards next-generation AI methods for synthetic biology. Several positions are available in a new large multi-year project, the Virtual Laboratory for Biodesign (BIODESIGN), implemented in collaboration between FCAI and VTT Technical Research Centre of Finland.
Supported by a 2 million EUR grant from the Jane and Aatos Erkko Foundation, the BIODESIGN project aims for breakthroughs in AI techniques for protein design by combining the strength of novel deep learning models with AI-based design and human feedback in a Design-Build-Test-Learn cycle. The virtual laboratory is envisioned to have wide applications in industry (e.g., new biochemicals, biomaterials and drugs) and to help the transition to a carbon-neutral society.
Your experience and qualifications
We are looking for applications with a strong academic record in computer science, mathematics, or statistics. Solid research experience in one or more of the following fields is beneficial:
- AI-based design
- Deep learning algorithms
- Generative models
- Human-in-the-loop machine learning
- Collaborative AI
- Molecular modeling
- Reinforcement learning
- Structured prediction
We invite applications from early-career scientists at all levels: Doctoral researcher (PhD student), Postdoctoral researcher, and Research fellow.
Your network and team
The successful applicants will join a world-class research team where top AI researchers in FCAI (led by Professors Samuel Kaski, Juho Rousu and Vikas Garg) join forces with synthetic biology experts of VTT (led by Prof. Merja Penttilä).
Links of PIs
Samuel Kaski:
https://research.aalto.fi/en/persons/samuel-kaski
Juho Rousu:
https://research.aalto.fi/en/persons/juho-rousu
Vikas Garg:
https://research.aalto.fi/en/persons/vikas-garg
Example publications of the PIs
- Brogat-Motte, L., Flamary, R., Brouard, C., Rousu, J. and d’Alché-Buc, F., 2022. Learning to predict graphs with fused Gromov-Wasserstein barycenters. In International Conference on Machine Learning (pp. 2321-2335). PMLR.
- De Peuter, S. and Kaski, S. 2023. Zero-shot assistance in sequential decision problems. AAAI-23
- Sundin, I. et al. 2022. Human-in-the-loop assisted de novo molecular desing. Journal of Chemoinformatics, 14:86.
- Ingraham, J., Garg, V., Barzilay, R., and Jaakkola, T. Generative Models for Graph-Based Protein Design. In Neural Information Processing Systems (NeurIPS), 2019.
- Garg, V., Jegelka, S., and Jaakkola, T. Generalization and Representational Limits of Graph Neural Networks. In International Conference on Machine Learning (ICML), 2020.
- Mercatali, G., Freitas, A., and Garg, V. Symmetry-induced Disentanglement on Graphs. In Neural Information Processing Systems (NeurIPS), 2022.
Ready to apply?
If you want to join our community, please submit your application through our recruitment system Workday by using the link on Aalto University’s web page ("Apply now” at the end of the page).
The deadline for applications is 7th May 2023 at 23:59 Finnish time (UTC +2).
Please note: Aalto University’s employees and visitors should apply for the position via our internal system Workday -> find jobs (not external aalto.fi webpage on open positions) by using their existing Workday user account.
To apply, please share the following application materials with us:
- CV
- Letter of motivation
- Applicants to PhD student position: transcripts of the MSc degree studies
Contacts: Fang Wang (
fang.wang@aalto.fi)
Aalto University reserves the right for justified reasons to leave the position open, to extend the application period, reopen the application process, and to consider candidates who have not submitted applications during the application period.
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