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development. To integrate the image processing pipeline in a modular way, building on algorithms developed by your colleagues. To optimize performance and throughput and use software engineering best practices
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promising pathway for fully decarbonized polymer precursors. Job description includes; Design and optimize Perovskites (doped and in-situ exsolved) for enhanced OER in solid oxide electrolysis process to
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To optimize suitable analytics to follow the physicochemical recycling process To create energy efficient dissolution and low-temperature depolymerization pathways for high quality footwear recycling
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design, optimization, and triage Conduct in-depth SAR analysis, combining experimental and in silico data towards the design of therapeutics Apply and supervise structure- and ligand-based design
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engineering of the polymer/monomer purification steps. The main objectives are: To gain physicochemical insights in the interaction between polymers present in footwear and solvents/reagents To optimize
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, repairability, reuse, and/or recycling. Numerical and/or experimental analysis and modelling of machine components with the aim of improving their durability, reliability, and optimizing performance, and energy
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nature, involving optimization, control, data science, and/or machine learning problems will be evaluated positively. An interest in issues related to the challenge of the transition will also be
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) mouse model to improve outcomes. A successful project will result in: A developed and optimized mouse EVLP platform. AI-based identification of 3 IRI and 3 rejection target genes expressed
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resources, funding, and mentorship Your Responsibilities: Lead the design, development, and optimization of scalable AI inference pipelines Implement and experiment with LLMs, GNNs, multi-modal AI, and vision
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, specifically by critically evaluating and further optimizing existing components of the preprocessing pipeline, such as peak detection, retention time alignment, and data normalization. This will help reduce