Tampere University and Tampere University of Applied Sciences create a unique environment for multidisciplinary, inspirational and high-impact research and education. Our university community has its competitive edges in technology, health and society. https://www.tuni.fi/en

The Faculty of Medicine and Health Technology (MET) is dedicated to pursuing world-class research and delivering high-quality education in the fields of biomedical engineering, biotechnology, medicine and health technology. We conduct internationally acclaimed basic and applied research. 

Job description

We are looking for a talented and motivated Postdoctoral Research Fellow to join our research team at the Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE). The researcher will focus on applying machine learning (ML) techniques to knowledge graphs (KGs) for advancing projects in chemical safety, toxicology, and drug discovery. This position is ideal for a candidate with expertise in knowledge graphs, graph embeddings, and ML techniques such as link prediction, neural networks, and recommendation systems. The applied position located in Tampere University will be filled fixed term for 2 years.

The main tasks are:

• Lead tasks in EU projects 
• Build Knowledge graphs (data collection, data extraction, data curation)  
• Development of machine learning methodologies for learning tasks on knowledge graphs (e.g., graph embedding, link prediction, and node classification). 
• Collaborate with interdisciplinary teams, including biologists, chemists, and computational scientists, to tailor ML solutions to specific project needs. 
• Publish high-impact papers and contribute to the dissemination of research findings through presentations and workshops. 
• Student supervision 

Requirements

• Applicable doctoral degree in a field such computer science, data science, artificial intelligence, bioinformatics or a related field with a strong computational focus.  
• Data Integration and Management: Experience working with large, heterogeneous datasets and integrating them into knowledge graphs. 
• Knowledge Graph Expertise: Strong experience with knowledge graphs, including their construction, querying, and management (e.g. Neo4j and Cypher) 
• Graph Embeddings and Link Prediction: Hands-on experience in generating graph embeddings (e.g., Node2Vec, TransE, etc) and performing link prediction tasks. 
• Machine Learning and Neural Networks: Proficiency in ML techniques, including graph neural networks (GNNs), and frameworks like TensorFlow, PyTorch, or scikit-learn. 
• Experience with extracting knowledge from text with NLP methodologies 
• Programming Skills: Proficiency in Python, with experience in graph libraries such as NetworkX, DGL, PyTorch Geometric, or Neo4j. 
• Ability to work independently and within an interdisciplinary research team
• Fluency in spoken and written English.
• Excellent teamwork and interpersonal skills.

We also appreciate:

• Familiarity with toxicological and pharmacological datasets (e.g., OMICs, adverse outcome pathways). 
• Experience with semantic technologies (e.g., RDF, OWL, or ontology development). 
• Background in deploying machine learning pipelines and APIs for real-world applications. 

Tampere University is a unique, multidisciplinary, and boldly forward-looking community. Our values are openness, diversity, responsibility, courage, critical thinking, and learner-centeredness. We hope that you can embrace these values and promote them in your work.

We offer

We offer a dynamic and collaborative research environment with opportunities to contribute to high quality research and the development with experts in computational science, biology and chemistry. Opportunities to work on cutting-edge interdisciplinary research projects at the intersection of machine learning, knowledge graphs, and toxicology. Support for professional development, including presenting at conferences and building collaborations.

The planned starting date is as soon as possible.   The position is full-time, and it will be filled for a fixed-term period for 2 years. A trial period of 6 months applies to all new employees.

The salary will be based on both the job requirements and the employee's personal performance in accordance with the salary system of Finnish universities. According to the criteria applied to teaching and research staff, the position of a Postdoctoral Research Fellow is placed on the job demands levels 5-6. A typical starting salary of Postdoctoral Research Fellow is around 3800-4400 EUR/month.

We are inviting you to be a part of a vibrant, active, and truly multidisciplinary research community. We value interdisciplinarity, as it allows you to expand your research network and exposes you to new perspectives and ideas to solve complex research problems and pursue novel research findings. We are strongly committed to the highest level of scientific research and the provision of high-quality education.

As a member of staff at Tampere University, you will enjoy a range of competitive benefits, such as occupational health care services, flexible work schedule, versatile research infrastructure, modern teaching facilities and a safe and inviting campus area as well as a personal fund to spend on sports and cultural activities in your free time. Please read more about working at Tampere University. You can also find more information about us and working and living Tampere by watching our video: Tampere Higher Education Community - our academic playground. 

Finland is among the most stable, free and safe countries in the world, based on prominent ratings by various agencies. Tampere is the largest inland city of Finland, and the city is counted among the major academic hubs in the Nordic countries. Tampere region is the most rapidly growing urban area in Finland and home to a vibrant knowledge-intensive entrepreneurial community. The city is an industrial powerhouse that enjoys a rich cultural scene and a reputation as a centre of Finland’s information society. Tampere is also surrounded by vivid nature with forests and lakes, providing countless opportunities for easy-to-access outdoor adventures and refreshment throughout the year. 

Read more about Finland and Tampere: 

• Visit Finland
• This is Finland
• Visit Tampere
• Welcome to Tampere
• International House Tampere

How to apply

Please submit your application through our online recruitment system (link below). The closing date for applications is March 28th, 2025 (23:59 EET / UTC +2). Please write your application and all accompanying documents in English and attach them in PDF format.

Please attach only the following documents to your application: 

• CV (according to TENK guidelines) including contact details of two referees
• A letter of motivation describing why you are interested and how your profile matches the candidate requirements and the research topics of our team. 
• PDF copies of your Doctoral degree certificates, including transcripts of all university records in original language. If original language is other than Finnish, Swedish or English, please provide an official translation in one of those languages.
• List of publications 

For more information, please contact:

Professor Dario Greco, dario.greco@tuni.fi

University Lecturer Angela Serra, angela.serra@tuni.fi

Postdoctoral Research Fellow Michele Fratello, michele.fratello@tuni.fi

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