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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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• 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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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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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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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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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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analysis activities for cooperation projects and clinical analysis. Engaging on the optimization of lipidomics/oxylipin (phospho) proteome analysis methods. You hold courses independently within the scope
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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