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for their expression in plant colonizing bacteria and integrating them into the chromosomes of appropriate chassis. Control systems will be designed to restrict expression to target plants and ensure optimal expression
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applicants for a 6-month paternity leave replacement who have a strong interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental
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inland, short-sea, and high-seas shipping routes. The project seeks to deliver industry-relevant tools that enable optimal design and operation of greener vessels, backed by real-world demonstrations
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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emphasis on research infrastructure and technology rather than preparation for an academic career path. You will be involved in research, but more focused on learning and improving how computing, workflows
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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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Associate, you will develop AI-enhanced Digital Twins for solar energy systems, enabling real-time monitoring, predictive maintenance, and performance optimization. You will design modular architectures
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national and international partners Maintain, calibrate and troubleshoot high-end mass spectrometers with a focus on GC-HRMS and Orbitrap analysers Develop, optimize, and validate analytical GC-MS and LC-MS
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prototype (MIDAS) that integrates AI-based modules with optimisation engines to support low-carbon, cost-optimal datacentre microgrid design. To manage prototyping of the software platform - overseeing build
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problem-solving skills and the ability to collaborate with cross-functional teams are essential. Responsibilities The main responsibilities of the role are as follows: Develop and optimize algorithms