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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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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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screening and automation for strain optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support sustainable biomanufacturing. (Bio)pharmaceuticals: Processing science and
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in at least two projects related to scale up and optimization of biomass valorization processes from wood and agriculture feedstocks for textiles and packaging applications. The portfolio of projects
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skills and experience in written, spoken, and collaborative work in English. What we offer: A career path optimized for transition to industry. You will be affiliated with the dynamic Aalto Scientific
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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
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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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been shown to accelerate and improve the training procedure of SNNs by defining new cost functions that are differentiable and easier to optimize. They can also handle quantized weights, e.g., using
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optimizing their performance in high-energy-density applications. The coated LFP materials should exhibit superior mechanical and chemical resilience, ensuring that the coatings maintain their structural
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tools that enable optimal design and operation of greener vessels, backed by real-world demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI