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supply system evaluate how different data sources and modelling choices affect predictive performance and practical usefulness contribute to scientific publications and doctoral thesis work in the field
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minni.forss@aalto.fi . We will go through applications, and we may invite suitable candidates to interview already during the application period. We aim for a prompt evaluation process, with both positions
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the call, e.g. geography, geoinformatics or landscape and spatial planning. The evaluation is based on the quality and potential of their research merits, teaching merits, academic leadership skills and
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methods for tunable metasurfaces that provide rapid sensitivity/gradient evaluation, support high-dimensional design spaces, and allow systematic optimization of performance targets such as efficiency
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. To create efficient adjoint-based optimization methods for tunable metasurfaces that provide rapid sensitivity/gradient evaluation, support high-dimensional design spaces, and allow systematic optimization
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and development projects based on your interests and needs. The preferred staring date for this position is in the Spring or Summer of 2026. The initial contract period is 2 years, evaluated by a
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successful candidate will be responsible for setting learning objectives, developing creative teaching methodologies, evaluating student performance, and processing feedback. In a team-oriented environment
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for a candidate ) General instructions for applicants including evaluation criteria, language requirements and guidelines for compiling your documents are given at Interested in joining our tenure track
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among all group members. Stay up to date with the latest HPC, AI, and general computing/data management practices, evaluate latest developments, and implement whatever is most suitable. Possibility
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technology assessment and scenario modelling Techno-economic evaluation Sustainability analysis and life cycle assessment Uncertainty-based investment pathway modelling Multi-criteria decision making