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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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background in geomodelling, geophysical and geotechnical investigation, geomechanical engineering, and machine learning. You will be expected to work effectively on a geophysical/geomechanical project, to
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, computer graphics, and embodied AI, including physics-based simulation, character animation, motion synthesis, and learning-based control for humanoid systems. Key Responsibilities: Conduct independent and
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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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Proficiency in Cadence Proficiency in Python and Matlab Experience in implementing algorithms for machine learning Good written and oral communication skills We regret to inform you that only shortlisted
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(DFT) simulations and develop machine learning potentials to investigate zeolite-related systems. The role will focus on delivering research projects and promoting research excellence in this area. The
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platforms, including robotic systems, laboratory automation, and AI/machine learning-assisted approaches for experimental design, optimization, and materials discovery. The research will target advanced
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electrochemical and CO2 removal research. Electrochemical process on interface phenomena MOF synthesis, testing under different conditions Simulation of scaled up process. Interface with machine learning group
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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/ The research fellow will work closely with PI Patrick Rebentrost on developing novel quantum algorithms