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-spectral microscopy framework that extracts meaningful spectral information from a single image, by combining innovative optical system design with learning-based data processing. The research aims
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extraction to support discovery. Collaborate with researchers to identify opportunities where generative AI and LLMs can accelerate scientific progress. Work with the Head of the Machine Learning Expertise
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machine learning processing of the spectroscopic data • The optical design and development of novel custom spectroscopic sensors benefitting from freeform optics. • Integration of the in-situ
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that reduce raw data at the sensor level. You will develop AI and machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability
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fairness and inclusion, racialized students often face barriers that harm their learning and well-being. Research has revealed many causes of these inequalities, such as socio-economic disadvantages
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. You can work in a group as well as on your own initiative. You have knowledge in machine learning for vision. Hands-on experience with image acquisitions and different types of cameras (visible
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experience with data analysis Enthusiastic team player Basic understanding of immunology Desirable but not required Experience in single-cell or spatial data analysis Machine learning experience Key personal
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is a plus Knowledge of network environments is an asset Key personal characteristics Structured and detail-oriented Eager to learn and able to persevere when facing technical challenges Communicative
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that ingest raw on-chain data (blocks, transactions, smart-contract events) from public blockchains into research-grade databases Developing statistical, graph, and/or machine learning models to study
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that he/she can check approve your file . You will have to upload some documents Proof of enrolment as a PhD student at your home University A signed Learning Agreement. Please chose the correct template