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of imaging protocols (MRI, MRS, OPM-MEG). Candidates will benefit from a demonstrable experience in these fields. The core abilities and attributes required include resilience, creative problem-solving
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researcher position is affiliated with two EU projects (TRUSTING - and DELTA-LANG) that concern themselves with medical applications of speech technologies to prevent clinical worsening in patients with mental
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, engineers, computer scientists, nuclear medicine physicians, …) towards the overall aim of enabling translational and physician-in-the-loop AI for medical imaging. Our research team is multicultural and
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and offering training opportunities for specialist clinicians and clinical scientists. The LifeArc and MDUK-funded Translational Rare Disease Centre to Treat Mitochondrial Diseases (LAC-TreatMito-UK
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the Neurogenesis and Brain Cancer group led by Prof. Simona Parrinello. The team uses a variety of state-of-the-art technologies, including advanced imaging, single cell and spatial ‘omics’, barcoding, mass
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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applications from candidates who meet the following criteria: PhD (or about to complete) in relevant discipline e.g. Bio/Medical/Mechanical Engineering; a track record of developing validated computational
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neurobiology and mouse models is advantageous. Have experience with in vivo calcium imaging (preferably 2-photon), stereotactic surgery and drug delivery, gene expression analysis (e.g. snRNAseq) and antisense
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Ref NumberB02-09130Professional ExpertiseResearch and Research SupportDepartmentSchool of Life & Medical Sciences (B02)LocationLondonWorking PatternFull timeSalary£43,374 £51,860Contract TypeFixed
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interdisciplinary team will develop a machine learning based monitoring system that leverages spoken language processing (SLP) and natural language processing (NLP) of speech recorded at home to calculate relapse