To establish a sound research base within The Alan Turing Institute in order to pursue individual and collaborative research of outstanding quality, consistent with making a full active research contribution in line with the research strategy outlined by the PI; To write or contribute to publications or disseminate research findings using other appropriate media; To attend and present research findings and papers at academic and professional conferences, and to contribute to the external visibility of the Institute; To participate in and to develop internal and external partnerships, for example, to identify sources of funding, generate income, obtain projects, or build relationships for future activities; To ensure compliance with secure handling of data and health and safety in all aspects of work
PhD in Machine Learning, Computational Statistics, Applied Mathematics, Computer Science, or a closely related discipline; A strong background in at least two of the following: Bayesian Decision Theory/Statistics; Probabilistic Machine Learning; Programming in Python & R; Experience in application, development and implementation of learning algorithms
Toggle navigation English (UK) Login Login Password Recovery Research Associate in Risk Modelling for Digital Twins Alan Turing Institute London United Kingdom Research Programmes Share Apply Company Description The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. The Institute is named in honour of the scientist Alan Turing and its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better. Position We are seeking to recruit a postdoctoral research associate to work on robust planning and robust routing algorithms that integrate combinatorial optimization methods with Bayesian decision theory to quantify uncertainty and estimate risk for the SDA (Sir David Attenborough) Digital Twin. There are open questions and research directions for how to best perform planning and routing under (multiple) uncertainty (sources). Full and efficient integration of routing optimization methods with full probabilistic treatments (i.e. multiple non-Gaussian predictive densities characterising epistemic and alleatoric uncertainty) and their intersection with Bayesian Decision Theory is an open research ground. The candidate will collaborate with teams at the University of Warwick (Warwick Machine Learning Group) and British Antarctic Survey (BAS, routing and planning algorithms) to perform original methodological work with an impactful application to the SDA Digital Twin. The ideal research associate will possess a PhD in machine learning, Baysian statistics, computer science, computational statistics or applied mathematics. Other quantitative backgrounds with relevant prior experience will also be considered. ROLE PURPOSE This post is an appointment to the Ecosystem of Digital Twins initiative within the programme on AI for Science and Government . The projects under this programme focus on research in data science, with accompanying translational activities to ensure impact in the fields of applied science, engineering and urban analytics governance, in keeping with the vision, mission and charitable aims of the Turing Institute. The role will also be associated with the Lloyd’s Register Foundation funded programme on Data-Centric Engineering within The Alan Turing Institute. The research associate will join a vibrant team of researchers affiliated with The Alan Turing Institute DUTIES AND AREAS OF RESPONSIBILITY The research associate will work closely with the Principal Investigator with the aim: To establish a sound research base within The Alan Turing Institute in order to pursue individual and collaborative research of outstanding quality, consistent with making a full active research contribution in line with the research strategy outlined by the PI. To write or contribute to publications or disseminate research findings using other appropriate media. To attend and present research findings and papers at academic and professional conferences, and to contribute to the external visibility of the Institute. To participate in and to develop internal and external partnerships, for example, to identify sources of funding, generate income, obtain projects, or build relationships for future activities. To ensure compliance with secure handling of data and health and safety in all aspects of work. OTHER DUTIES Some Teaching may be required as part of collaboration work Requirements PhD in Machine Learning, Computational Statistics, Applied Mathematics, Computer Science, or a closely related discipline. A strong background in at least two of the following: Bayesian Decision Theory/Statistics Probabilistic Machine Learning Programming in Python & R Experience in application, development and implementation of learning algorithms Ability to initiate, develop and deliver high quality research aligned with the research strategy indicated by the PI and any industrial stakeholders and to publish in peer reviewed journals and conferences. A developing track record in producing high quality academic publications Please see the job description for a full breakdown of the duties, responsibilities and person specification Other information APPLICATION PROCEDURE If you are interested in this opportunity, please click the apply button below. You will need to register on the applicant portal and complete the application form including your CV and covering letter. If you have questions about the role or would like to apply using a different format, please contact us on 020 3862 3575 or 0203 862 3340, or email email@example.com . CLOSING DATE FOR APPLICATIONS: 4 October 2022 at 23:59 We reserve the right to close this vacancy early or to interview suitable candidates before the closing date if enough applications are received. TERMS AND CONDITIONS This full-time post is offered on a / fixed-term basis for 12 months. The annual salary is £38,000-£42,000 plus excellent benefits, including flexible working and family friendly policies, https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant at a salary of £34,500 per annum EQUALITY, DIVERSITY AND INCLUSION The Alan Turing Institute is committed to creating an environment where diversity is valued and everyone is treated fairly. 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