Wissenschaftliche Mitarbeiterin/Wissenschaftlicher Mitarbeiter für Maschinelles Lernen/KI (w/m/d)

About

The Technische Hochschule Würzburg-Schweinfurt (THWS) is one of the largest practice-oriented universities in Bavaria, covering a broad spectrum of subjects with its fields of technology, social and economic sciences, design, and languages. We support around 9,300 students in more than 70 degree programs on their educational path. Since 2022, THWS has been certified by the audit familiengerechte hochschule to accommodate the diversity of life plans and family structures and to actively promote the compatibility of work and family for its employees. The Kitzingen Technology Transfer Center (TTZ-KT) at THWS focuses on the areas of robotics, artificial intelligence, and digitalization. We currently collaborate with 25 regional partner companies, from SMEs to global corporations, in various industries such as production, logistics, software development, and construction companies. Our international team is led by two experienced research professors and currently employs five research associates.

We currently have the following position to fill:

Technologietransferzentrum Kitzingen Research Associate for Machine Learning/AI (m/f/d) Full-time Application Reference Number: 24.7.776

The position is to be filled as soon as possible, with the place of work in Kitzingen. The employment is initially limited until December 31, 2027, and full-time (40 hours/week). An extension is planned; the position is generally suitable for part-time work, provided that the full scope of duties is ensured through job sharing.

Do you want to contribute your knowledge, skills, and experience to exciting research and development projects in the field of AI and machine learning? Do you enjoy working in a practice-oriented manner and collaborating with companies? Then this position is exactly right for you!

Responsibilities

The following exciting tasks await you:

• Conducting applied research in the field of Artificial Intelligence, often in collaboration with industry partners
• Developing solutions, including using modern machine learning and classical artificial intelligence methods
• Writing research proposals
• Representing the Technology Transfer Center in public relations
• Publishing results in scientific journals and presenting them at national and international conferences and workshops
• Supervising final theses and project work for Bachelor's and Master's students
• For Master's graduates, we offer the opportunity for a doctorate in our doctoral center "Sustainable and Intelligent Systems (NISys)"

Qualifications

• Successfully completed scientific university studies (e.g., Master's or University Diploma) or doctoral studies, preferably in the fields of Artificial Intelligence, Robotics, Computer Science, Applied Mathematics, or a related field, or a comparable relevant qualification
• Experience in one or more of the following research areas:
  • Large Language Models (LLMs) / Vision-Language Models (VLMs)
  • Representation Learning (including Diffusion Models)
  • Neural Networks
  • Statistical Learning
  • Reinforcement Learning
  • Planning and Optimization
  • Application of AI for Time Series Analysis or Predictive Maintenance
• Programming skills, especially in robotics and AI/ML (Python, C++, Julia)
• Experience with modern deep learning frameworks such as Tensorflow/PyTorch
• Professional experience in industry and robotics knowledge (ROS) are advantageous
• Strong communication and social skills
• Good German language skills, both written and spoken, at least at B1 level

Benefits

• Varied and challenging tasks with flexible working hours through a flexitime account and a generous home office policy
• 30 days of annual leave
• The attractive benefits of the public service
• Collegial cooperation in a highly motivated team with flat hierarchies and an open communication culture
• Diverse opportunities for training and further education
• Free parking facilities
• Discounts in the cafeterias of the Studierendenwerk Würzburg
• An attractive university city with a high quality of life
• Health promotion measures such as subsidized sports courses, health days, and workshops

The employment and remuneration are based on the relevant regulations of the collective agreement for the Länder (TV-L) with all customary benefits of the public service. Classification will be in pay group 13 TV-L, provided all requirements are met.

Severely disabled applicants will be given preference in case of otherwise essentially equal suitability, qualification, and professional performance.

Our university welcomes applications from women who feel particularly addressed by this advertisement.