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shape relational aspects of work. Identify the mechanisms through which AI-mediated contributions and autonomous agents reshape relational dynamics, and develop evidence-based guidance for responsible and
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ethnography, interviews, observation or longitudinal qualitative research. Ability to study work practices and ethical dynamics in organisational settings, requiring close interaction with participants, strong
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and/or IB theories, discussing the dynamics of change both between and within platforms and ecosystems. Many of the project’s empirical cases have been planned to focus on the retailing sector. However
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and/or Python; experience with Unix/Linux environments and bash is considered an advantage Prior experience in the preprocessing, analysis and interpretation of omics data and a strong interest in
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, or otherwise as agreed, for a fixed-term ending latest in August 2030 – a Finnish PhD thesis project typically takes around four years. Position description This PhD project will perform a coordinated analysis
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software (e.g., Quantum ESPRESSO). Molecular dynamics packages (e.g., LAMMPS). Machine learning interatomic potentials (e.g., GAP, MACE, NequIP ). Machine learning libraries and frameworks such as Scikit
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integrates materials chemistry, formulation, and interfacial analysis with electrochemical characterization, supported by advanced characterization techniques, to elucidate structure–processing–performance
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, or another relevant field Strong skills and experience in handling and analyzing ecological or environmental data Experience with data handling and analysis in R Experience in working with spatial datasets
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and analyzing ecological or environmental data Experience with data handling and analysis in R Experience in working with spatial datasets, either with R or GIS programmes or equivalent Excellent