About The Role
To undertake directed research activity as part of an EU project called ExtremeXP (Experiment driven and user experience-oriented analytics for extremely precise outcomes and decisions) under the direction of Prof Hamid Bouchachia. The project will develop Scenario-driven and opportunistic machine learning with the aim to (1) design and develop AutoML mechanisms for performing scenario-based algorithm and model selection considering on-demand user-provided constraints (performance, resources, time, model options), (2) devise mechanisms for continual learning in algorithm and model selection: as new data sets become available, the so-far learned selection strategies are continuously adapted.
We are seeking to fill the position with a talented and enthusiastic candidate with at least a master’s degree having excellent analytical, programming, communication and scientific writing skills, who will contribute to the delivery of the project by designing, conducting the proposed research and producing published outputs. Candidates must have strong analytical background in Machine Learning preferably with good exposure to Meta-learning, Continual Learning, AutoML, Scalable ML and Trustworthy AI. The project will target new and original ML algorithms and strategies leading to exploitable constraint-aware ML and analytics services.
This position is available on a fixed-term basis for 4 months.
This position does not meet the eligibility requirements for sponsorship under the Skilled Worker Route within the UK Visa and Immigration service’s Points Based System. Therefore, BU will not be able to sponsor individuals who require permission to work to carry out this position. For more information, please visit UK Skilled Worker Visa.
About The Department
Our vibrant Faculty of Science & Technology encompasses a wide range of disciplines across six departments: Archaeology & Anthropology, Computing & Informatics, Creative Technology, Design & Engineering, Life & Environmental Sciences, and Psychology. The breadth of subject areas means our cutting-edge research is delivering real benefits to the environment, our economy, health and improving cyber security. Our staff are given the opportunity to travel the world to contribute their expertise to expeditions and projects being led by other academic institutions and private organisations, as well as taking the lead on their own research projects, is helping us to understand our past, protect and preserve our environment for the future and support creative and digital industries to grow and develop.
The research associate will be affiliated with the Data Science & Artificial Intelligence Group based at the Computing & Informatics Department. The group is very dynamic, ambitious, well networked and delivers state-of-the-art research in a range of machine learning and data science topics, publishing research results in prestigious venues.
About Us
Bournemouth University’s vision is worldwide recognition as a leading university for inspiring learning, advancing knowledge and enriching society through the fusion of education, research and practice. Our highly skilled and creative workforce is comprised of individuals drawn from a broad cross section of the globe, who reflect a variety of backgrounds, talents, perspectives and experiences that help to build our global learning community.
BU values and is committed to an inclusive working environment. We seek a diverse community through attracting, developing and retaining staff from different backgrounds to contribute to inspirational learning, advancing knowledge and enriching society. To support and enable our staff to achieve a balance between work and their personal lives, we will also consider proposals for flexible working or job share arrangements.
A job description for this position is available at the top of this page. If you require this in a different format, please contact us at hrvacancies@bournemouth.ac.uk.
Please append to your application form a 1 to 2 page motivation letter followed by a CV (including publication list if any).
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