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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, a position is available as of 1 November 2026 within the third-party-funded project āHUMKIT ā Telepresence Platform for HUMan-centred AI-supported
Maintenance Technologies (STEP Early-Career Research Group of the SAB)
Research Assistant (m/f/d)
Reference number: 61-2026
on a part-time basis (0.5 FTE), on a fixed-term contract until 31 October 2028, with the possibility of extension subject to the availability of funding.
HUMKIT is developing a human-centred, AI-supported telepresence system for industrial maintenance and diagnostic processes, which integrates mobility, sensor technology, navigation and psychological requirements in complex production environments. Within the project, early-career researchers are conducting interdisciplinary research into new technical, organisational and AI-based solutions to make remote maintenance more efficient, safer and more resource-efficient, thereby strengthening the competitiveness of industry.
Your areas of responsibility:
- Development of robust, interpretable AI models for the analysis of heterogeneous sensor data
- Implementation of AI-supported detection of obstacles, environmental changes and anomalies in production environments
- Real-time support for robot navigation through adaptive decision-making models, warning systems and recommendations for action
- Integration of user knowledge and environmental knowledge into ML models (knowledge-informed AI)
- Validation and evaluation of AI methods in terms of robustness, transparency and practical applicability
- Collaboration with sensor technology, production engineering, psychology and XR development to implement a human-centred telepresence system
Your profile:
- A degree in Computer Science, Mathematics, Natural Sciences or Engineering
- In-depth knowledge of machine learning, ideally in interpretable and robust ML methods
- Experience in handling heterogeneous sensor data (image, depth, motion, biosignals) and image and video processing
- Good knowledge of Python and common ML frameworks (e.g. PyTorch, TensorFlow)
- Interest in knowledge-informed ML and the integration of expert knowledge into AI models
- Ability to collaborate across disciplines with sensor technology, production engineering, psychology and XR teams
- An independent, analytical and solution-oriented approach to work
- Very good written and spoken English
What we offer:
- a salary, depending on individual qualifications, up to pay band E13 under the TV-L pay scale
- An attractive workplace 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 facilities as part of the workplace health management scheme
Mittweida University of Applied Sciences is committed to a balanced staff structure. Applications from people of all genders are therefore welcome. Furthermore, 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. Applications from people with severe disabilities and those of equivalent status are welcome and will be given preferential consideration 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/
