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Field
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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out together with seven industrial partners and is externally funded by the Knowledge Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods
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experimental collaborators. The position is part of the Research Council of Finland project ELPH-ML (https://research.fi/en/results/funding/88752 ). In combination with academic development courses at Aalto
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of Finland project ELPH-ML (https://research.fi/en/results/funding/88752 ). In combination with academic development courses at Aalto University, we will help you grow a competitive and international career
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expert in modelling: what matters most is your passion for human physiology, your curiosity about cancer cells behaviour, and your willingness to develop new computational skills along the way
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AI-Based Forecasting Models We invite applications for a PhD position focused on developing next-generation AI-based forecasting models to enhance renewable energy (RES) integration into power systems
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mathematical and/or algorithm development backgrounds are especially sought. KIOS Research and Innovation Center of Excellence (KIOS CoE) The KIOS Research and Innovation Center of Excellence operates within
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(e.g. Agentic Reinforcement Learning), evaluation, tool use, agentic harness, or retrieval-augmented systems. Internship/full-time experience from research, engineering, or algorithm-development roles in
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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, focusing on the development of algorithms for proactive decision support in non-stationary warehouse environments. This project aims to study warehouse efficiency across interdependent processes – including