429 developer-"https:" "https:" "https:" "UCL" "UCL" Fellowship positions in Singapore
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clinical needs through the development of innovative disruptive health technologies and bring them from the bench to the bedside, thus benefitting patients and society. We are seeking a Research Fellow with
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also work closely with the Principal Investigators to help supervise and train junior lab members and to ensure smooth functioning of an active research program. The candidate will have the opportunity
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Singapore’s AI-for-Science ecosystem. Key Responsibilities: The candidate is expected to conduct the following research works Develop and optimize multimodal LLM/MLLMs for downstream tasks (adaptation
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Responsibilities Develop and implement Python‑based AI/ML models (e.g. LSTM or time‑series models) to predict long‑term properties of bioactive materials. Conduct independent testing on restorative and bioactive
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tools using modern statistical and data science approaches, and take a substantive role in the development of peer-reviewed scientific manuscripts, with opportunities for lead or co-authorship depending
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manuscripts. Contribute substantially to grant development, particularly NMRC and other national or international funding schemes, through study design, analytics planning, and generation of compelling
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compiling, result analysis etc. Perform research-related administrative tasks and assist in day-to-day management of laboratory. [For Research Fellow] must be able to train lab members, write manuscripts and
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research papers, present research outcomes, conceptualise new ideas and develop plans for independent research which could have a considerable influence and impact on the relevant field attracting research
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Key Phenotypic Definition and Evaluation, including molecular and biochemical bioassays Characterization of Genetic Control Cultivar and Lines Development Integration of Genomic Data into Cultivation
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models, focusing on industrial image analysis Develop advanced deep learning methods for power battery inspection models Design and implement novel algorithms for AI-based CT imaging Lead experimentation