297 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at Nature Careers in United States
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or plasmapheresis machines Experience in a blood donor center or plasma center Job Responsibilities: Independently perform and report pre-analytic and post-analytic activities for waived testing. Resolve donor
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basic science to its effective translation for preventing or alleviating disease. Candidates for this joint appointment should have research interests focused in computational immunology/AI/Machine
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for learning and growth, you can shape a career path that is right for you while also enjoying all the benefits and stability of working for a world-class institution. This includes work-life balance with
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for sickle cell disease and CAR T-Cell therapy applications. The HAL is composed of two sections, the Quality Control Section providing product analysis by flow cytometry, product quality testing for sterility
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systems; setup and configuration of computers and printers in a networked environment; maintenance of hardware components and computer peripherals) preferred Knowledge of Video Conference & AV equipment
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, military branch, conflict counselling). Experience in data entry and working in emergencies and fast pace, stressful environment. Some experience with computer systems, including Microsoft Office (Word
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(such as a laptop computer or tablet). Work may involve possible exposure to malodorous vapors, low dose radiation, contamination by toxic chemicals and acids and presence of carcinogenic substances or other
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collecting relevant data from 2D, 3D or 4D images. Perform computer automated analysis and quality control on large data sets. Liaise effectively with other groups at Janelia to manage multiple image analysis
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research. Initially, jET interns will be dedicated to learning engineering tools and best practices by assisting staff engineers and scientists in ongoing work. Later on, jET interns will be expected to work
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to integrating computational simulation, data science, and deep learning technologies to deeply explore structure–property relationships in materials. Its goal is to drive the precise design and development of new