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sufficient to carry out image processing and data analysis. Skills in hypothesis-testing, experiment design, analysis of data sets and writing scientific manuscripts and reports. Demonstrate enthusiasm
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, communications, science and technology. Our students are at the heart of everything that we do, and we are committed to supporting them to pursue their career and personal ambitions. Our research is engaged
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-The-Shelf (COTS), all-digital radar systems linked to an array of ultra-stable, ultra-low phase noise oscillators. The project is part of the UK Quantum Technology Hub in Sensing, Imaging and Timing (QuSIT
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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techniques, image analysis, genetic manipulations, biophysical approaches, and collaborate with theoreticians to address these questions. The specific details and aims of the project will be driven by
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the Portfolio Manager and Clinical Director & Academic Lead. Areas of current projects for example are: Artificial intelligence for imaging interpretation Medical technologies for stroke characterization Case
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quantum technologies since 2014 and now leads the UK Quantum Technology Research Hub in Sensing, Imaging and Timing (QuSIT). Bringing together academic partners from seven universities, the British
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for successful candidates to join are listed below. BRC Theme: Cardiovascular / Imaging & Engineering Supervising Principal Investigator: Professor Alex Rothman Research project area: Pulmonary Hypertension (PH
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Job Description Position Details School of Chemistry, College of Engineering and Physical Sciences Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally