Junior Scientist AI (all genders)

Karlstad University

Österreich

Vor Ort

EUR 41.000 - 49.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden
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Benefits dieser Stelle

Relocation support
Training opportunities
Family-friendly policy
Meal allowance
Klimaticket subsidy
Open door policy

Zusammenfassung

SAL is seeking a researcher to join its Embedded Systems group in Austria, focusing on trustworthy AI for industrial and scientific partnerships. You will advance anomaly detection, predictive maintenance, and learning methods across domains, prioritising safety and reliability while collaborating with peers in cross-disciplinary teams.

You will contribute to federated learning, reinforcement learning, and automata learning, applying AI techniques to manufacturing, electronics, and energy

Qualifikationen

  • Master's degree in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Data Science, Physics, or a related field.
  • Strong programming skills in Python.
  • Experience with code management tools such as Git (GitLab).
  • Experience with frameworks such as PyTorch and TensorFlow.
  • Experience applying statistical techniques to analyse data and detect outliers.

Aufgaben

  • Conduct innovative research in your field of expertise and address challenging scientific questions.
  • Analyse research questions and design methods with senior experts.
  • Design and carry out experiments, simulations and research activities; evaluate results.
  • Translate research findings into practical AI technologies and applications.
  • Present results within the team and at conferences; contribute to publications and reports.
  • Follow developments and expand expertise through training and professional development.

Kenntnisse

Python
Machine learning
English
Communication

Ausbildung

Master's degree (CS/Robotics/EE/Applied Math/Data Science/Physics)

Tools

Git (GitLab)
PyTorch
TensorFlow
Data analysis

Jobbeschreibung

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As part of SAL's Embedded Systems research team, you will be responsible for developing and testing resilient and trustworthy AI in applied research projects with industrial and scientific partners, as well as colleagues from other SAL units.

You will support research and development in areas such as advanced anomaly detection, out-of-control action planning, predictive maintenance algorithms and automata learning.

You will contribute to the development of scalable, distributed AI and learning methods, such as federated learning, federated distillation and reinforcement learning, and apply these techniques across domains including manufacturing, electronics and energy, while prioritising safety, reliability and trustworthy AI practices.

Your future tasks include:
  • Conduct innovative research in your field of expertise and investigate new approaches to address challenging scientific and technological questions.
  • Analyse research questions and application requirements, identify suitable methods and develop solutions in collaboration with experienced colleagues and senior experts.
  • Design, plan and carry out experiments, simulations and research activities, and critically evaluate and interpret the results.
  • Translate research findings into practical solutions and contribute to the development of innovative technologies and applications.
  • Present and discuss your results within the research team, at scientific conferences and with external partners.
  • Contribute to scientific publications, technical reports, reviews, project proposals and research documentation.
  • Follow current scientific and technological developments and continuously expand your expertise through research, training and professional development.
  • Build a strong scientific profile and develop towards becoming a recognised expert in your field.
  • Actively contribute to knowledge exchange and foster collaboration across interdisciplinary research teams.
Your profile:
  • Master's degree in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Data Science, Physics, or a related field.
  • Good programming skills in Python.
  • Experience with code management tools such as Git (GitLab).
  • Experience with frameworks such as PyTorch and TensorFlow.
  • Experience of applying statistical techniques to analyse data, detect outliers and select and sample datasets.
  • Good knowledge and a proven track record in machine learning, including classical methods such as SVMs and decision trees, as well as deep learning methods such as LSTMs, CNNs and transformers.
  • Specific experience in Large Language Models (LLMs) and Generative AI, Embedded AI and TinyML, Reinforcement Learning, Formal Methods and Automata Learning.
  • Experience with edge platforms (Raspberry Pi, NVIDIA Jetson).
  • Fluency in English is essential; knowledge of German would be advantageous.
  • Good communication skills, including basic presentation and academic writing skills.
Important Facts about SAL:
  • Diverse research activities with many technical challenges.
  • State-of-the-art laboratory facilities and equipment.
  • Location in the heart of Europe in Austria - relocation support for non-European nationalities.
  • Internal and external training opportunities for career development.
  • Family & children friendly - actively shaping the compatibility of family and career.
  • "Vital4SAL" to promote a healthy workplace (e.g. SAL coaching pool, trainings on mental health, physical activities, healthy snacks, 24/7 accident insurance)
  • € 4 per day meal allowance in restaurants or € 2 per working day in supermarkets.
  • Public transport initiative (subsidy for the "Klimaticket")
  • Our values: Open door policy, flexibility in working hours, casual dress code, diverse teams, working with people of different nationalities, informal communication, lifelong learning, compatibility of family and career, sustainability, personal growth, and collective advancement.

This position is subject to the Collective Agreement for employees in non-university research (Research CA) starting in occupational group E. We offer competitive salaries and additional benefits based on your experience and qualifications. For this position, your minimum monthly salary starts with EUR 4.056, paid 14 times a year.

In the network of science and industry, we carry out research at the highest global research level.

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