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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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- “Reliable industrial foundation models for trustworthy industrial robot fault diagnosis in automotive smart manufacturing”. He/She will be required to: (a) carry out research in advanced machine learning
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statistical methodology, including genomic prediction, crop simulation and machine learning, to improve prediction of crop yield and related traits. Supervision and Researcher Development: Assist with mentoring
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for full Stokes vector detection. The candidate will focus on optical simulation, cleanroom nanofabrication, device integration, optoelectronic testing, and machine learning-driven signal reconstruction
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opportunity to learn from our highly interdisciplinary, collaborative, and dynamic research group that meets regularly and includes leading scientists (and other fellows) with expertise in several disciplines
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geophysical investigation, geomechanical engineering, and machine learning. The Centre for Urban Solutions is to provide leadership in developing innovative solutions and sustainable technologies for space
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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• PhD in Mathematics/Statistics/CS. Skills: • Proficiency in reinforcement learning, quantitative finance, risk management, and machine learning. • Strong programming skill in Python
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environment for our students, staff, and community by reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader
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interpretable machine learning framework that integrates diverse biological data—including transcription factor (TF)–DNA interactions, epigenomic features, and three-dimensional (3D) genome organization