28 machine-learning "https:" "https:" "https:" Fellowship research jobs at Nanyang Technological University
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phase-field simulations. Experience in developing AI or machine learning models for physics-based scientific or engineering applications. Proficiency in Python, scientific computing and machine learning
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experimental optimization, structure–performance analysis, and/or mechanistic investigations. Familiarity with machine learning techniques, optimization algorithms, and data-driven approaches for materials
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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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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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and remote sensing imagery for ecosystem monitoring. Develop machine/deep learning-based workflows to interpret ecosystem disturbance. Synthesize model simulations and multi-source observations
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at NTU are looking for a Research Fellow (RF) to carry out in research in probabilistic machine learning, causal discovery and GenAI, by exploring cutting-edge approaches such as causal representation
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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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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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to conduct research, solve complex technical problems, and develop innovative solutions. Experience with parallel systems, machine learning/AI, or performance benchmarking is highly desirable. Ability to work
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geological modelling and/or geophysical imaging Familiarity with site investigation, borehole logging, and geophysical approaches Experience with machine learning or deep learning is preferred Good written and