Research Infrastructure Specialist AI/ML with focus on Materials Science
Workplace: Uppsala, Sverige
Expires: August 29, 2025
A position at Uppsala University for a research infrastructure specialist in artificial intelligence and machine learning focused on materials science, supporting advanced computational resources and AI Factory Service Hub initiatives.
Main requirements:
- PhD in materials science, physics, chemistry, computer science, or related field
- Documented experience applying AI/ML methods in natural sciences or engineering
- Proficiency in programming (e.g. Python, TensorFlow, PyTorch, scikit-learn)
- Ability to work in interdisciplinary teams and communicate with technical and non-technical stakeholders
- Fluent professional English in both spoken and written form
Responsibilities:
- Support researchers in materials science with data management, software, and AI/ML tools on national and European AI Factory computational resources
- Develop and implement AI/ML methods for advanced materials science problems
- Collaborate with research groups to identify AI/ML needs and opportunities
- Contribute to the development of AI infrastructure and tools within the AI Factory Service Hub
- Participate in training, workshops, and knowledge transfer activities within academia
- Document and disseminate results through scientific publications and technical reports
Required hard skills:
- PhD degree in relevant scientific disciplines
- AI/ML method application in science and engineering
- Programming skills in Python and AI/ML libraries (TensorFlow, PyTorch, scikit-learn)
- Data management and handling large-scale datasets
- Scientific communication in English
Recommended hard skills:
- Experience with high performance computing (HPC) or EuroHPC environments
- AI/ML applications in material design, simulations or experimental data analysis
- Large scale data curation including databases, metadata, FAIR principles
- Collaboration with industry or EU projects
- Teaching experience at university level
Soft skills:
- Good social skills and collaboration ability
- Initiative and independent working skills
- Effective communication with interdisciplinary teams
- Adaptability and eagerness to learn
Coding languages:
- Python
Frameworks:
- TensorFlow
- PyTorch
- scikit-learn
Operating systems:
- Linux (common in HPC and scientific computing environments)
Natural languages:
- English (Proficient)
- Swedish (Basic familiarity)
Cultural skills:
- Experience working in European research infrastructure projects
- Academic collaboration and networking
- Engagement in multidisciplinary scientific environments
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