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    Data Scientist Research - Lowestoft, Suffolk, United Kingdom - Centre for Environment, Fisheries and Aquaculture Science

    Centre for Environment, Fisheries and Aquaculture Science
    Centre for Environment, Fisheries and Aquaculture Science Lowestoft, Suffolk, United Kingdom

    4 weeks ago

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    Description
    Organisation Centre for Environment, Fisheries and Aquaculture Science Locations Lowestoft, UK

    Application Deadline 39 days remaining Salary £ 51,685 - £58,105 The Centre for Environment, Fisheries and Aquaculture Science (Cefas) is a world leader in marine science and technology, providing innovation, scientific evidence and impartial expert advice on the aquatic environment, biodiversity and food security.

    You will work across our science themes of Animal and Human Health, Ecosystem Change, Environment and People, and Food from Water, playing a prominent role in driving forward Cefas data science and AI capability.

    You will provide creative and strategic technical leadership to build and deliver research involving AI, machine learning, computer vision, data analysis, and scientific computing.

    This includes current projects on end-to-end applications of cameras and automated image analysis for monitoring, and establishing new areas, for example, in the use of large language models.

    The work will involve large, unstructured data sets, with you collaborating closely with IT colleagues to specify and deploy high performance computing and data storage infrastructure.

    You will have opportunities to build national and international research collaborations, with an expectation of regularly publishing your work.

    You will develop and lead projects and supervise colleagues to deepen Cefas' technical expertise and promote innovation to make a difference to our understanding of the aquatic environment.

    The role requires hands-on technical skills, coupled with thought leadership and strategic planning.

    Through these activities you will play a leading role in enhancing Cefas' external profile in the use of data science in global marine and environmental research.

    Cefas is proud of a diverse and inclusive work environment, committed to fairness and the promotion of equality of opportunity for all.

    We know that having a range of experiences, backgrounds, ways of working and thinking, makes us a stronger organisation, better at reflecting the communities we serve.

    We welcome applications from candidates who have not previously worked for the Civil Service, mid- and late-career changers with transferable skills, people from all backgrounds and circumstances regardless of disability, gender, age, ethnicity, LGBT+ identity and socio-economic status.

    Leading research on the development and deployment of innovative data science and AI methods and hardware to transform data collection and analysis within Cefas science;
    Delivering as a Principal Investigator, leading research proposals and projects with multi-disciplinary teams;
    Publishing high-quality scientific papers on new methods and applications;

    Establishing, developing, and maintaining strategic collaborations with other government bodies, academia and commercial partners; Using detailed technical knowledge to provide advice to senior leaders on AI strategy and application, working with IT specialists to specify big data storage and scientific computing requirements.

    Deep technical knowledge of data science and AI methods, with evidence of creatively leading research topics and programmes involving bespoke data collection and analysis;
    Ability to lead, mentor, and train others, ensuring the integrity and accuracy of data analyses, along with evidence of working with specialists from different disciplines to deliver to deadlines;
    Having a broad knowledge of science and computing to help design robust Enterprise solutions provided by Cefas IT professionals;

    Evidence of national and international research networks, working with external organisations to develop new research and attract funding; Deep technical knowledge of data science and AI methods, maintaining knowledge of new developments, with an excellent record of publications in peer-reviewed journals, and/or patents and reports.

    Excellent scientific computing and programming skills, including Python and version control, for processing big data. Experience on Linux and Windows, ideally including Microsoft Azure.
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