The University of Vaasa and ELLIS Institute Finland: Call for Professors in AI research in space applications, machine learning and energy and optimisation
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The University of Vaasa, together with ELLIS Institute Finland, is inviting applications for three tenure track positions in Artificial Intelligence research, focusing on space applications, machine learning, energy and optimisation. The application deadline is 9 March, 2025.
The School of Technology and Innovations, along with ELLIS Institute Finland, seeks outstanding candidates to the following positions in AI research and its various applications:
Assistant/Associate/Full Professor
- in AI in Space Applications
- in Artificial Intelligence/Machine Learning – Energy Systems
- in Balancing Energy and Optimisation for HPC
These Principal Investigator (PI) positions are jointly offered by the University of Vaasa and ELLIS Institute Finland, a newly established world-class research hub in AI and Machine Learning. Launching in 2025, ELLIS Institute Finland is the second institute of ELLIS, the pan-European AI network of excellence. In collaboration with universities across Finland, the Institute is now recruiting Principal Investigators (PIs) to lead research teams in AI, machine learning (ML) and related fields. This is a unique opportunity for researchers at all career stages to do work with global impact in a research environment that is one of the best in the world today for AI and ML.
More information about the requirements and how to apply at ELLIS institute web page. The positions are also described below.
1) Assistant/Associate/Full Professor in Space Applications
The University of Vaasa is seeking applications for a tenure-track Professor position in AI for Space Applications. This position offers an exciting opportunity to drive research and innovation at the intersection of artificial intelligence (AI), machine learning (ML), space technologies, and the evolving space economy, with a particular emphasis on new space business models and their role in the energy transition. The position focuses on advancing AI-driven solutions for satellite-based solutions, autonomous systems, and intelligent data processing to support sustainable and commercially viable space technologies and applications.
2) Assistant/Associate/Full Professor in Artificial Intelligence/Machine Learning – Energy Systems
The Cyber-Physical Systems (CPS) Research Group is seeking applications for a tenure-track Assistant Professor position in Artificial Intelligence (AI) and Machine Learning (ML). This position offers an exciting opportunity to contribute to research and innovation in the intersection of AI, ML, and CPS, with a particular emphasis on applications in energy transition technology.
3) Assistant/Associate/Full Professor in Balancing Energ and Optimisation for HPC
We are seeking applications for a tenure-track Assistant Professor position in Artificial Intelligence (AI) and Machine Learning (ML). If a suitable candidate is found, the position may be filled as a PS Fellow position. This position offers an exciting opportunity to contribute to research and innovation in the intersection of AI, ML, and Computer Science, with a particular emphasis on Energy efficient High Performance Computing (HPC).
Requirements
Applications are invited for tenure track positions at all levels (Assistant Professor, Associate Professor and Professor) in the following areas: Space Applications, Artificial Intelligence/Machine Learning (Energy Systems), and in Balancing Energy and Optimisation for HPC. Candidates should hold a doctoral degree in a relevant field and have a strong research background in academia. Regular publication in top-tier AI-driven venues is espected.
More information about the requirements and how to apply at ELLIS institute web page.
Further Information
As regards the position in Space Applications, further information on the position and the working environment may be obtained from Vice Rector Mika Grundström (tel. +358 29 449 8786, email: mika.grundstrom@uwasa.fi) or Professor Heidi Kuusniemi (tel. +358 29 449 8504, email: heidi.kuusniemi@uwasa.fi).
As regards the positions in Artificial Intelligence/Machine Learning and Balancing Energy and Optimisation for HPC, further information on the positions and the working environment may be obtained from Dean Raine Hermans (tel. +358 29 449 8622, email: raine.hermans@uwasa.fi) and Professor Mohammed Elmusrati (tel. +358 29 449 8275, email: mohammed.elmusrati@uwasa.fi).
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