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intelligence (AI) to optimize large dataset analysis, improving decision-making processes for awarding grants to firms and scientists. Key research areas include: Enhancing Selection Decisions: How can we make
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pharmacology. The PhD project will focus on testing and optimizing antisense oligonucleotides in preclinical in vitro models, as well as formulating these molecules into a novel biodegradable delivery system
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to carry out high-quality research on the modelling of power system balancing process for future sector-coupled European energy systems. The task will include assessment of reserve requirements and
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effective enzymatic recycling processes. We are looking for candidates with strong qualifications in some of the following areas, and a motivation to develop within others: Protein chemistry Enzyme kinetics
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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funded PhD scholarships (3-year employment) in a vibrant interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization for light trapping in thin
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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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Method to analyze the single-photon source performance (PhD1). Optimize and propose new single-photon source designs overcoming these limitations to be fabricated by other PhD students (PhD1). Perform
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for realistic haptic control and feedback, real-time agent-based simulation for guiding optimal work task performance. Following smart serious gaming approaches, novel artificial intelligence forecasts human
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems