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- Fundació per a la Universitat Oberta de Catalunya
- AMBER laboratory
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combines synthetic biology, machine learning, and biosensor and pathway dynamic regulation design to produce next-generation bio-based chemicals. The Computational Synthetic Biology group (CSBG), led by Dr
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/funding reference: PID2021-124030NB-C31 Job title: Optimization, learning, and cooperation with applications in logistics Research line / Scientific-technical services: Optimization in transportation and
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theory and experiment. By integrating quantum optics, quantum information theory, and machine learning, the project seeks to establish scalable hybrid spin–orbit quantum links. Free-space connections
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work. Availability for a ≥4 month stay abroad. Background in at least one of: AI/machine learning, computational modelling, microscopy, or cell/molecular biology. LanguagesENGLISHLevelGood Additional
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. Preliminary exposure to machine/deep learning, statistical modelling or generative AI. Application process: Interested candidates are invited to apply via the PHYNEST online platform by submitting a full CV, a
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analysis, including statistics and machine learning techniques. Proficiency in scientific programming, especially Python and/or Matlab, and experience in shell scripting. Excellent written and oral
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the project ‘MultiLearn: A multimodal approach to language learning: a window into the linguistic skills of children with neurodevelopmental disorders‘. The project is led by researchers Alfonso Igualada and
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Offer Description We are seeking a PhD student to develop the project ‘MultiLearn: A multimodal approach to language learning: a window into the linguistic skills of children with neurodevelopmental