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low-valent main group compounds with unique electronic structures and studying their reactivity, particularly boron-containing p-block molecules. Key Responsibilities: Research/project progress Data
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hydrodynamic modelling and sediment transportation. ii. Model Validation: Validation of DHI Mike Model with past historical data iii. Data Analysis: Process and analyze coastal and ocean wave data to improve
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-world deployment in ambient intelligence and clinical informatics. Publish in top-tier conferences and journals (e.g., NeurIPS, ICML, MLSys, IEEE TPAMI, JBHI). Job Requirements: Preferably PhD in Computer
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by using explainable AI To develop generative AI techniques to design novel biologics for cancer Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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equivalent qualifications/experience High level analytical capability Ability to communicate complex information clearly Essential criteria: Demonstrated research experience with publications in top journals
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hydrodynamic modelling and sediment transportation. Model Validation: Validation of DHI Mike Model with past historical data Data Analysis: Process and analyze coastal and ocean wave data to improve model
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work on a translational project and generate preliminary data for a PhD. Examples of programmes on-going include using peripheral immune cells to predict immunotherapy response in biliary tract and liver
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Requirements: A PhD degree in mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data Proficiency in programming languages such as
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, natural sciences, computing, informatics and computer science. A PhD (or near to completion) or equivalent experience in Biological or Biomedical sciences, Immunology or Bioinformatics High level analytical
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the field of the project High level analytical capability Ability to communicate complex information clearly Willingness to work flexibly and out-of-hours when necessary, to fulfil the needs of the research