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, innovation, and translational potential. The successful candidate will work on integrative projects involving in vivo mouse models, tumor immunobiology, and multi-omic profiling, with particular attention
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annum inclusive of Oxford University weighting Potential to under fill at grade 06RS: £34,982-£40,855 per annum inclusive of Oxford University weighting The Department of Computer Science seeks to employ
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deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing
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how ponds work for water quality benefits and translating findings to help guide design and management of urban stormwater ponds. The postdoc will work collaboratively with the project PIs, students and
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UCLA is known worldwide for the breadth and quality of its academic, research, health care, cultural, continuing education and athletic programs. UCLA offers undergraduate degrees in more than 127 majors
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designing and translating technology into the clinical. This role will be supported by the Quality Management Systems team at London Institute for Health Care Engineering who will collaborate closely with
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international meetings and conferences Work closely together with other experimental and computational researchers in the group Assist with training and supervising other researchers (e.g. student assistants, BSc
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Knowledge, Skills, and Abilities PhD in Neuroscience is required. Experience with in vivo imaging in head-fixed behaving mice is required. Experience with Arduino microcontrollers for the design and control
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, Genetics, Cell Biology, Biophysics or a related field - Competency in computational (R or Python) and statistical analysis - Competency in experimental design and standard molecular biology, imaging
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials