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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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no more than four years before the start of employment. For well-justified reasons (e.g., parental leave, military or civil service), this limit may be extended. Selection will be based on an overall assessment
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, candidates should have completed their doctorate no more than four years before the start of employment. For well-justified reasons (e.g., parental leave, military or civil service), this limit may be extended
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related field. Strong knowledge of machine learning. Strong publication record in a relevant field. Excellent analytical and problem-solving skills. Interest in collaborative research with both academia and
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on developing novel Machine Learning methods for financial markets. The positions will offer excellent opportunities to work in a team of professionals responsible for developing cutting-edge technologies in
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ownership of open-ended problems The following are seen as advanteges but not necessary: Experience working with unstructured data sources (e.g. documents, long-form text) Familiarity with machine learning
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growth and yield studies. Knowledge of different digital data collection tools, statistical approaches, machine learning and AI-based techniques, forest growth modelling and simulation systems, as
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more than five years ago at the time of accepting the position. In this context, the 5-year limit refers to a net period of time, which does not include maternity leaves, parental leaves, military service
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processing, machine learning, statistics or related fields. Demonstrated expertise in ML/AI, with prior experience of applications in the healthcare domain, particularly in cancer research considered a strong
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establish independent research groups at FIMM and contribute to the development and application of cutting-edge statistical and machine learning methods in molecular medicine and population health. This group