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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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or electrochemical system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be preferred Good oral and
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to cell and gene therapy. Will learn to use advanced manufacturing tools and strategies to gain a deeper understanding of challenges associated with T cell-based immunotherapies (such as CAR-T cells). Will
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PhD qualification degree in Electronic Engineering or Computer Science Familiarity with pinching antennas and machine learning Good written and oral communication skills Proficiency in python
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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-focused engineers to contribute to our successful railways-applied smart machines research programme. About the Role We are seeking a highly motivated and multiskilled Research Fellow with expertise in
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focusing on the integration of machine learning, wafer-scale synthesis of materials. The role will contribute to the university's research mission by conducting fundamental research, helping secure external
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++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in
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processing and statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; Work on sleep datasets
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to £43,805 per annum Apply by: 26/04/2026 Role Description We welcome applications from skilled, delivery-focused engineers to contribute to our successful railways-applied smart machines research programme