Research Assistant. - Institute of Data Science 26/Sa02

Unist Berlin

Stellenbeschreibung:

Offer Description

At the University of Greifswald’s Institute of Data Science in the Faculty of Mathematics and Natural Sciences, there is a job vacancy from 10April 2026, subject to the allocation of funds, for a full-time

Research Assistant.

The position is to be filled for a limited period of 36 months . Payment will be made according to pay group 13 TVL Wissenschaft . The position is suitable for part-time employment.

Germany is undergoing profound demographic change, characterised by an ageing population and declining birth rates. This development is accompanied by an increase in age-related chronic diseases nd thus a significant growth in the need for long-term care. The increase in cognitive impairments such as mild cognitive impairment and dementia, which require a high level of care, is particularly serious. At the same time, the shortage of nursing staff is reaching alarming proportions. In view of these challenges, innovative solutions are needed.

The BehAIve project will make a promising contribution in this area. It aims to develop an AI-supported, situation-adaptive system to support older people in their everyday lives or geriatric patients during hospital stays. Continuous monitoring using sensors will analyse subjects’ behaviour, identify problematic behaviour and offer targeted support where necessary. This can significantly improve the quality of life of people with cognitive impairments or geriatric patients while also reducing the workload of nursing staff. The sub-project ‘Scalable Systems for multimodal Data Analysis’ deals with the development and implementation of methods for automatic knowledge extraction, multimodal behaviour analysis and language-based interaction.

Job Description:

  • Development of scalable systems for automatic knowledge extraction and learning of planning models from textual data
  • Development of scalable systems for language-based interaction
  • Development of scalable systems for activity and situation recognition from sensor data
  • Development of multimodal sensor systems for the recording of human behaviour
  • Publication of the obtained results in scientific journals and conferences

Job Requirements:

  • University degree (masters or comparable) in artificial intelligence, data science or another related discipline, by the time employment starts
  • Practical experience in machine learning, especially deep learning and its practical application in the domain of sensor analysis
  • Practical experience with multimodal sensor systems
  • Practical experience in the field of natural language processing, especially large language models, prompt engineering, finetuning, retrieval augmented generation (RAG), and GraphRAG approaches
  • Hands on experience with Python
  • Excellent English language skills, and
  • Motivation to join an interdisciplinary and international research environment.

This vacancy is open to all persons, irrespective of gender. Severely disabled applicants with the same qualifications will be considered with preference.

In accordance with § 68(3) PersVG M-V, the Staff Council will only be involved in staff matters of the academic or artistic staff on request.

Unfortunately, application costs (e.g. travel expenses for interviews) will not be reimbursed by the state of Mecklenburg-Vorpommern.

Please note that by submitting your application, you provide your consent pursuant to data protection law for our processing of your application data. Further information about the legal bases and the use of your data can be found here.

Applications comprising all usual documents must be sent with reference to the job advertisement number 26/Sa02 by 15 February 2026 , preferably via email (one PDF file), to:

#J-18808-Ljbffr
NOTE / HINWEIS:
EnglishEN: Please refer to Fuchsjobs for the source of your application
DeutschDE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung

Stelleninformationen

  • Veröffentlichungsdatum:

    04 Feb 2026
  • Standort:

    Berlin
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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