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Field
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data, including biomedicine and drug discovery. The position gives excellent opportunities in publishing in high-quality forums. We expect the applicants to have a PhD degree (or close to completing one
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space-based astronomical image slicing spectrograph. The goal is to create and apply a 'digital twin' of the as-built system to simulate and optimize its performance. Key responsibilities include
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, cold chain logistics, and sustainable packaging systems, addressing critical challenges in product protection, supply chain optimization, and distribution system efficiency. We seek a highly motivated
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the most informative polarimetric parameters and optimal wavelengths for detecting abiotic stress. This approach will contribute to more accurate digital phenotyping, supporting sustainable crop monitoring
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assessment of CCUS value chains Reactor design, optimization, and sizing using phenomenological and/or CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with
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(or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply
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. The group will be contributing to the Physics Modeling (MC software, MC validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous
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of vegetation–climate–technology interactions to optimize energy yield in environments subject to climatic stress. Responsibilities: Monitoring PV panels: temperature, efficiency, dust accumulation. Using
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skills for functional genomic screen design and analysis. You will build CRISPR tools, design optimized pooled genetic screens (e.g. Perturb-seq–based approaches), and troubleshoot the experimental
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computational approaches to biological systems. Its core activity is the development of deep learning methods for protein design and optimization, with applications in biology and medicine. - activities: We