10 machine-learning "https:" "https:" "https:" positions at Heriot Watt University in United Kingdom
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of pursuing external funding. Experience of computational chemistry techniques. Experience in cheminformatics, machine learning and/or algorithm development for chemical synthesis. Experience with UNIX and HPC
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information please visit the TransiT website https://transit.ac.uk/. We are seeking a proposal for a project contributing to Digital Twin Development this work involves computer programming and data analysis
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buildings closed days (and Christmas Eve when it falls on a weekday).. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by
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‑of‑the‑art computational featurisation with experimental reaction‑kinetics data to build a machine‑learning platform capable of predicting catalyst performance. This is an exciting, highly collaborative
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team of 12 technical staff. The mechanical workshop has a range of machinery including conventional workshop equipment (lathes, mills etc.) CNC machines, 3D printers and other tooling. The role holder is
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Role: Assistant Professor in Mathematics and Digital Learning Grade and Salary: Grade 7, £37,694 - £47,389 per annum FTE and working pattern: 1FTE, 35hrs per week, Monday – Friday Contract: 24
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and engineers. Key Responsibilities 1. AI Model Development & Testing Assist in developing machine learning and deep learning models for medical imaging analysis. Implement and fine-tune models using
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) School of Mathematical and Computer Sciences FTE and working pattern: 1FTE, Full time - 35 hrs per week Location: Dubai Campus The School of Mathematical and Computer Sciences has been teaching both
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committed to an equality charter (see https://www.hw.ac.uk/about/our-schools/mathematical-and-computer-sciences/about-us/our-equality-charter ), which includes having a diverse and inclusive workforce, and
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. Qualifications Minimum: Master’s degree in engineering or a related discipline (e.g., Mechanical, Electrical, Computer, Energy, Materials, Mechatronics). Preferred: PhD’s degree in a relevant field. Prior