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on processing and developing representation models for diverse data sources, including time-series data (EEG, video, mass spectrometry) and chemical data (molecular graphs, SMILES strings) related to odorant
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inherent complexities. Your role: The doctoral student will conduct research at the intersection of optimization, game theory, and automatic control for complex systems. Their work will encompass both
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3 Oct 2025 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Computer science » Programming Computer science » Other Mathematics » Applied mathematics Mathematics
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adaptation, emission reduction targets, and equity considerations. The methodological approach will combine theory-driven and data-driven modeling with an aim to construct AI systems grounded in behavioral
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issues. knowledge in process modelling and material/energy balances programming skills (Python) qualitative research methods, innovation theory, socio-technical systems theory After the qualification
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their ability to: independently pursue his or her work collaborate with others, have a professional approach and analyze and work with complex issues. Experience in machine learning, algorithmic theory, or code
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of ecological processes involving animals and plants across a range of spatial and temporal scales understanding of raster data processing including the theory and implementation of relevant algorithms
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sustainability demands of future AI-driven applications. Together, these positions provide unique opportunities to advance both theory and applied technologies in 6G, while contributing to standardization
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. In this doctoral project, you will contribute to the theory formation for mobile sub-THz and THz wireless communication systems for 6G and beyond and establish yourself at the international forefront
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develop new communication theory and signal processing algorithms. The goal will be to develop theory, algorithms, and network architectural concepts to deliver ubiquitous network services across the globe