AALBORG

Ansøgningsfrist: 09.06.2025
Afdeling: Department of Computer Science
Ref. nummer: 2025/130
Are you passionate about probabilistic machine learning and its potential to address real-world scientific challenges? At Aalborg University, Denmark, we invite you to join a collaborative project at the intersection of advanced probabilistic machine learning and microbial bioscience. This position offers a unique opportunity for developing novel probabilistic ML methods with a view towards bioinformatics and modeling of the complex microbial communities that shape our word.
We are seeking a highly motivated post-doctoral researcher to develop scalable probabilistic machine learning models and algorithms for representation learning, uncertainty quantification, and model interpretability over large, heterogeneous datasets such as sequenced microbial DNA fragments coupled with auxiliary environmental data.
The position is initially for one year, with the possibility of an extension for up to 2 years based on mutual agreement.
Starting date: August 15th, 2025, or soon thereafter.

QUALIFICATION REQUIREMENTS

Appointment as postdoc requires academic qualifications at PhD level.

WHO WE ARE

Aalborg is a lively city with numerous cultural attractions. The area features relatively low cost of living, clean air, beautiful forests and beaches, and very good transportation infrastructure. For more information see Visit Aalborg .
The Computer Science Department at Aalborg University takes a leading international position within data management and verification. It is a very young university (1974) but with a strong international profile in Mathematics, Computer Science & Engineering, also hosting the two most highly cited Computer Scientists of the country.
The department has a strong profile within artificial intelligence and machine learning. The AI-ML team at the department is a multidisciplinary group of researchers working on various aspects of AI and machine learning. The group gathers more than 40 researchers, covering diverse aspects of machine learning ranging from methodological developments to application-oriented research.
For further information, please contact Abdulkadir Celikkanat (abce@cs.aau.dk), Katja Hose (khose@cs.aau.dk), Andres Masegosa (arma@cs.aau.dk), or Thomas Dyhre Nielsen (tdn@cs.aau.dk).

This position is part of the VILLUM Synergy project “Illuminating microbial dark matter through data science”, an exciting cross-disciplinary probabilistic machine learning project with applications in bioscience. As part of the project, you will be involved in

• Conducting original research in probabilistic machine learning, within the topics mentioned above, focusing on generative and Bayesian models relying on methods ranging from mathematics, algorithmic design, to implementation, and experimentation.
• Analyzing large-scale environmental datasets to recover and explore microbial genomes.
• Collaborating with researchers in computer science and biosciences to produce original and high-impact research.
• Publishing your findings in top-tier international conferences and journals within machine learning and computer science.