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spectrometry techniques (QTOF, MALDI-TOF-TOF and triple quadrupole). Our ideal candidate will have: Experience in water, mass spectrometry and data engineer A PhD (or equivalent) in mass spectrometry related
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and visualisation. Identify and establish best practices in the patient pathway and referral network through utilisation of descriptive analytics. Use predictive analytics and machine learning to drive
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at the Medway campus, contributing to the delivery and development of our Digital Engineering and Innovation Portfolio such as Applied AI for Engineering, Robotics and Automation, Computer Engineering, Electrical
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of the following areas: Software Development Cyber Security Artificial intelligence Machine Learning Data Science Big Data Visualisation What we are looking for Enthusiastic academic professionals
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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contexts. They will be expected to contribute to the effective delivery of teaching, learning, and student support by: Delivering and evaluating classroom and practical teaching across modules Designing and
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machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role. This post would be ideal for an ambitious and
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/or machine learning methods, and an interest in applying these tools to urban and housing policy questions. The Fellow should demonstrate potential for producing high-quality research and a strong
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regenerative medicine, biosensing, and therapeutics. Learn more at www.stevensgroup.org . This post is available from October 2025 for a fixed-term of 18 months, with the possibility of part-time appointments