Reference Number: 60032369
Location: Bunhill Row
School: The Business School (formerly Cass)
Department: Faculty of Actuarial Science & Insurance
Contract Duration: Permanent
Hours: Full-time
Salary Range: (£) 38017 to 44045
Background
Founded in 1894, City, University of London is a global university committed to academic excellence with a focus on business and the professions and an enviable central London location. City attracts around 20,000students (over 40% postgraduate level) from more than 150 countries and staff from over 75 countries. In the last decade, City has almost tripled the proportion of its total academic staff producing world-leading or internationally excellent research. Led by President, Professor Sir PaulCurran, City has made significant investments in its academic staff, its estate and its infrastructure and continues to work towards realising its vision of being a leading global university. The Faculty of Actuarial Science andInsurance makes use of its position close to the heart of the City of London to enhance its research, teaching and external profile. Its research considers a range of theoretical and applied issues in statistics, general insurance, and health care.
We are seeking motivated, collaborative and self-starting individual with experience in statistical modelling with emphasis on regression techniques, and computational statistics. The role is a full-time ResearchFellow on a fixed-term appointment for three years and will be to support the development of a novel methodology for insurance and health care data, to name but a few. The role holder with work under the supervision of Professor RosalbaRadice (Business School, City, University of London) and Professor GiampieroMarra (Department of Statistical Science, University College London).
Responsibilities
Take responsibility for the statistics of a number of studies. This will include some or all of: contributing to development of novel statistical approaches,contributing to the development of a statistical software package which implements the novel approaches, undertaking statistical analyses, writing reports and papers, solving statistical problems that may arise, with support from senior colleagues.
Contribute to the development and dissemination of sound methodology appropriate to the group’s portfolio of studies.
Contribute to the writing of grant applications to generate income and where appropriate, take responsibility for the writing and publication of high-quality papers in peer-reviewed literature both nationally and internationally.
Liaise with colleagues within and external to the Business School andUCL and build networks for the exchange of information and to form relationships for future collaboration.
Person Specification
We are seeking motivated, collaborative and self-starting individual with experience in statistical modelling and computational statistics. Thesuccessful candidate will be enthusiastic with a strong work ethic, and who enjoys vigorous discussion, critical thinking and team working. It is essential to have strong statistical background, and R programming skills. Applicants will hold a PhD in Statistics (or related discipline).
Additional Information
City offers a sector-leading salary, pension scheme and benefits including a comprehensive package of staff training and development.
Closing date for applications: 11.59pm 12th May 2021
Interviews will be held on 27th May 2021
The start date for the project will be 1st July 2021
For informal enquiries, contact Rosalba Radice (< href="mailto:rosalba.radice@city.ac.uk">This email address is being protected from spambots. You need JavaScript enabled to view it.) and/or Giampiero Marra (This email address is being protected from spambots. You need JavaScript enabled to view it.)
For more information, please see
https://www2.i-grasp.com/fe/
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Professor Giampiero Marra
Department of Statistical Science
UniversityCollege London
GowerStreet, London WC1E 6BT
Giampiero Marra
Homepage for Dr Giampiero Marra, University College London. Contact details and background inf...
