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, with the possibility of renewal, in the field of Analysis and Partial Differential Equations (PDEs). Job description - The successful candidate will collaborate on research projects related
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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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analysis, and data visualization. Apply advanced statistical, machine learning and AI methods when appropriate. Review analysis outputs and ensure methodological consistency and quality. Collaborate with
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collaborate closely with the supervisory team and colleagues. This is what we ask of you You enjoy experimental research and want to work at the interface of physical chemistry, spectroscopy, photochemistry and
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for original or collaborative scholarship Scientific writing skills demonstrated through peer-reviewed publications Ability to acquire accurate, reproducible data Critical eye towards consistency
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About UM6P: Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning, that is committed to an educational system based on the highest standards
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contribute to a transdisciplinary collaborative project that aims to utilize multiple phases of data collection to create time-lapse images of the study area in the southern Rio Grande rift, New Mexico. The
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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to research projects involving LLMs and related AI systems, including collaborations with project partners, guidance to students, participation in and organisation of seminars and conferences, and development
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
Posting Description POSTDOCTORAL ASSOCIATE, KEATING LAB, Biology, to join a small, collaborative peptide design team working at the interface of computation and experiment. Working closely with