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a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A Ph.D. degree in Computer Science, Computer Engineering, Mechanical Engineering
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InLife Institute of Animal Reproduction and Food Research, Polish Academy of Sciences | Poland | 13 days ago
on the part of the controller. Are there any recipients of personal data? What are the categories of recipients? The recipients of candidates’ personal data will be entities authorised by law or processors
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, Skills, and Abilities Excellent written, verbal and computer skills required. Excellent communication and interpersonal skills. Must be able to work independently and/or collaboratively. Excellent critical
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of public health, biostatistics, pharmacoepidemiology and epidemiological studies. They must be proficient in data analysis using statistical or computer modelling software, such as Stata or R. They should
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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License/Registration/Certification n/a Physical Requirements Some standing or walking. Sitting at computer workstation for extended periods. Repetitive motion. Lifting, pushing, or pulling of objects up
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the equipment, including the annual budget and the personal computer provided by the MARBEC laboratory for modelling and mapping work. - main mission: The researcher’s main role will be to model and integrate
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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
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evaluation of machine learning, computer vision, and other algorithms, primarily in the context of health. They will be part of the thriving research community of Duke Spark (spark.duke.edu) where AI
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that can be repurposed for viruses with pandemic potential. This includes working closely with computer scientists to utilize published “omics” datasets and machine learning approaches to identify FDA