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Field
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of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science. Responsibilities Develop and deploy ML algorithms for autonomous operations and optimization
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disease progression. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will
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analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission management platforms, contributing to the deployment of smart UAV demonstrators under
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contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research
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, and inline interpretation. The work includes validating algorithms on a lab-scale sorting setup and linking spectroscopic outputs to recyclability scoring and Digital Product Passport data flows. Your
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5000 years as a background to the local reconstructions for target sites. This will be achieved using pollen databases, new pollen cores, and the landscape reconstruction algorithm (REVEALS and LOVE
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analysis across time and conditions Algorithm design and modeling. The role offers significant intellectual freedom and opportunities to shape the direction of the research. Minimum Qualifications: • PhD in
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
to develop/translate model algorithms and develop new model code in Fortran, d) software skills needed to work with multiple observed and model datasets, e) a strong desire/motivation to develop scientific
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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring