This page was translated automatically using artificial intelligence (DeepL). The German version is binding. More information about automatic translation
Facts and figures
To strengthen our team, a position is available from 1 November 2026 in the Computational Intelligence Group at the Saxon Institute for Computational Intelligence and Machine Learning (SICIM) at Mittweida University of Applied Sciences, as part of the externally funded project futuRNA-Sax ā Preparing for the Future of RNA-Based Diagnostics and Medicine in Saxony (STEP Early-Career Research Group of the SAB), we are seeking to fill the position of
Research Associate (m/f/d)
Reference number: 59-2026
on a part-time basis (0.5 FTE), on a fixed-term contract until 31 October 2028, with the possibility of extension subject to available funding.
The futuRNA-Sax project aims to develop a fully integrated pipeline comprising nanopore RNA sequencing, interpretable AI, Biophotonics validation and XR visualisation, in order to make functional RNA structures available for diagnostics and drug discovery more quickly, reliably and in a resource-efficient manner. At the same time, the project trains early-career researchers in Saxony in these key technologies, thereby strengthening regional innovation capacity, technology transfer and the future viability of the pharmaceutical and medical sectors.
Your areas of responsibility:
- Development of robust, interpretable AI models for RNA structure ensembles (clustering and classification methods)
- AI-supported validation of FRET-constrained RNA 3D structures and selection of plausible conformations
- Integration of a priori knowledge, biochemical relationships and structural hierarchies into AI models (knowledge-informed AI)
- Analysis of heterogeneous data sources (sequence, structure, FRET measurements) for structure selection and uncertainty assessment
- Development of energy- and data-efficient ML methods for RNA analysis
- Creation of AI interfaces to sequencing, XR and Biophotonics modules
- Experimental evaluation of the models in terms of robustness, interpretability and validity
- Collaboration with bioinformatics, Biophotonics and XR teams to implement an integrated RNA analysis pipeline
Our requirements:
- A degree in Computer Science, Mathematics, Bioinformatics/Biotechnology, Natural Sciences or Engineering
- In-depth knowledge of machine learning, ideally in robust and interpretable ML models
- Extensive experience with Python and ML frameworks (e.g. PyTorch, TensorFlow)
- Interest in knowledge-informed AI and the integration of biochemical or bioinformatics-structural expertise into ML models
- Ability to mathematically analyse heterogeneous data sources (sequence, structure, FRET measurements) and integrate them into ML models
- Analytical thinking, a structured approach to work and an enthusiasm for interdisciplinary research
- Willingness to collaborate with bioinformatics, Biophotonics and XR teams
- Good communication skills and motivation to familiarise yourself with an innovative, forward-looking field of RNA diagnostics
- Excellent written and spoken English
What we offer:
- a salary, depending on individual qualifications, up to pay band E13 under the TV-L collective agreement
- an attractive role with regular working hours and family-friendly working conditions
- Professional induction into the existing research infrastructure of SICIM at Mittweida University of Applied Sciences
- A motivated and friendly team
- attractive sports activities as part of the workplace health management programme
Mittweida University of Applied Sciences aims to increase the proportion of women in teaching and research and therefore expressly encourages qualified female candidates to apply. Persons with severe disabilities will be given preference where qualifications are equal. Relevant supporting documentation must be enclosed with the application.
Interested candidates are requested to submit their full application documents, quoting the reference number above, by 7 September 2026 at the latest to:
digitally: preferably as a single PDF file to karriere@hs-mittweida.de with the subject line āApplication, Reference Number, Nameā,
or by post:
Mittweida University of Applied Sciences
, Human
Resources Department, PO Box 1457, 09644 Mittweida
Notes and Privacy Policy
Please note: To ensure your application documents are returned to you, please enclose a suitable, sufficiently stamped return envelope. Please be aware that, as a precaution, any expenses incurred during the recruitment process will not be reimbursed.
Please note that, for security reasons, electronic applications or attachments to applications made via links (hyperlinks) to third-party websites for download cannot be considered as part of the recruitment process.
Data protection notice: Mittweida University of Applied Sciences collects your data for the purpose of conducting the application process and fulfilling pre-contractual obligations (Article 6(1)(b) of the GDPR). Data will be stored for six months following the conclusion of the process.
Further information on data protection can be found at: https://www.hs-mittweida.de/newsampservice/datenschutz/
