Doktorand:in im Bereich Maschinelles Lernen zur Integration von Virusdaten
Uni Jena, Germany
- Institution
- Uni Jena
- Country
- Germany
- Position type
- PhD
- Subject area
- Computer Science & AI
- Application deadline
- 9 November 2026
- Location
- Jena, Thüringen, DE
- Funding
- Fully funded position
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About this position
The Institute of Computer Sciences at the Faculty of Mathematics and Computer Science seeks to fill the position of a
Doctoral Researcher in Machine Learning for Virus Data Integration (m/f/d)
commencing on 01 January 2027. We offer a part-time position (50% or 75%, 20 or 30 hours per week), with a fixed-term employment until 30 June 2030.
The DFG-funded Collaborative Research Centre 1768 “VirusREvolution: Decoding tools for virus research” is a highly ambitious research centre at Friedrich Schiller University with the joint goal to develop novel tools for virus discovery, characterisation, regulation, interaction, and visualisation (https://virusrevolution.uni-jena.de/). Its integrated research training group is educating doctoral researchers in a structured, interdisciplinary training program and invites applications for doctoral and postdoctoral researcher positions in various fields of research.
In this doctoral project within the Junior Research Group “Machine Learning data integration from photonics to genomics”, you will design and train representation models and combine two or more of them in predictive deep fusion models. The goal of the project is the integration of different data that can describe viruses, from various omics to microscopy and Raman spectroscopy, in a common predictive deep learning framework.
Your responsibilities:
- Research in multi-modal representation learning and deep fusion models for data integration
- Participation in the Collaborative Research Centre VirusREvolution and close collaboration with the project partners
- Engage in regular discussions with other group and project members
- Collaborate with BSc and MSc students working in associated projects
- Publish papers and present your work at national and international scientific meetings
Your profile:
- A highly motivated candidate with a Master of Science or equivalent degree in computer science, bioinformatics, computational biology, or a related discipline
- Solid programming skills and experience with machine learning or deep learning are required
- Knowledge in data integration across different data modalities and virus biology is desirable
- Strong analytical thinking and problem-solving
- Ability to work independently and in a collaborative team
- Excellent skills in English are required, both written and spoken
We offer:
- Embedding in a cross-disciplinary, young research group and a large, ambitious research consortium
- Affiliation to an Integrated Research Training Group, offering close support and a comprehensive education program for hard skills and transferable skills, supported by the Jena Graduate Academy
- A family-friendly working environment with a variety of offers for families
- University health promotion and a wide range of university sports activities
- Remuneration based on the provisions of the Collective Agreement for the Public Sector of the Federal States (TV-L) at / up to salary scale E13 — depending on the candidate’s personal qualifications—, including a special annual payment in accordance with the collective agreement.
- 30 days of vacation per calendar year plus two days off on December 24 and 31
Candidates with severe disabilities will be given preference in the case of equal qualifications and suitability.
Are you eager to work for us? Then apply by November 9, 2026 using our online form.
For further information for applicants and the information on the collection of personal data, please refer to Data privacy and information for applicants
Apply directly to Uni Jena
Emerging Scholars Council is not the employer and does not recruit for this position. It is advertised by Uni Jena, and your application goes to them. We help students prepare and strengthen their applications.
Go to the official application page →Applications close 9 November 2026.