Assistant Professor in Applied Statistics or Actuarial Data Science
Directorate:School of Mathematical and Computer Sciences
Salary:Grade 8 (£46,735 - £57,422)
Contract Type:Full Time (1FTE), Open Ended
Detailed Description
The Department of Actuarial Mathematics and Statistics at Heriot-Watt University, Edinburgh, is seeking to enhance and expand its strengths in research and teaching in statistics by appointing an Assistant Professor in Applied Statistics or Actuarial Data Science. This is an open-ended position.
Applicants are invited from any area of applied statistics, including statistical or actuarial data science. Those working in actuarial science, Bayesian statistics, statistical learning and/or actuarial statistics are particularly welcome to apply. Candidates who would like to work with the University’s multi-disciplinary Global Research Institutes in the areas of either climate change and sustainability, or healthcare are also welcomed.
As a successful candidate, you will lead, carry out and publish internationally excellent research in your field. You will have a strong track record of research in applied statistics, actuarial or statistical data science which includes fields such as Bayesian statistics, statistical learning, actuarial statistics, computational statistics and statistical methodology.
You will either be established or have the potential to establish yourself as an international research leader, with strong postdoctoral research experience and the ambition to build a world-class academic group.
You will have the relevant experience to engage and innovate in our specialised actuarial, statistical, data science and financial teaching programmes.
The School strongly encourages and supports the generation of industry impact from research, and we welcome candidates with experience of statistical work with industrial partners or working with the actuarial/insurance/financial industry.
About our Team
The Department of Actuarial Mathematics and Statistics has a warm, supportive environment with staff from all over the world. The Department is internationally renowned in actuarial science, statistics and statistical data science, applied probability and financial risk, through its world-leading research activities. As part of the Maxwell Institute, we are ranked 3rd in the UK for the excellence and breadth of our research, in the 2021 UK government’s 5-yearly assessment of university research.
The Department is looking to further strengthen its actuarial science and statistics group, to support its ambitions to enhance and expand its expertise in these areas. Our staff work in various fields, such Bayesian statistics, applied statistics, statistical learning, actuarial statistics and epidemiology. We have close ties and collaborations with researchers at the School of Mathematics at the University of Edinburgh, through the Maxwell Institute, under the “Data and decisions” research theme.
In line with this, the Department is seeking to further its research contributions to the University’s Global Research Institutes (GRIs), particularly the two GRIs concerning climate change and sustainability, and healthcare. The GRIs are a means to address the multi-disciplinary research challenges in these fields, to connect and focus the research efforts of academics across the University.
In the University structure, the Department sits within the School of Mathematical and Computer Sciences, along with the Department of Mathematics and the Department of Computer Science. The School is a partner in the Maxwell Institute for Mathematical Sciences, an institute that brings together the mathematical research activities at Heriot-Watt University and the University of Edinburgh. The Maxwell Institute is an internationally pre-eminent, collaborative centre for research and for postgraduate training in the mathematical sciences. It offers an environment that can attract and foster the very best mathematical talent from around the world.
With an exciting programme of research events, the Maxwell Institute is the heart of mathematical sciences research in Edinburgh. It also coordinates the Maxwell Institute Graduate School (MIGS), to which all our mathematical sciences PhD students belong. The Maxwell Institute was awarded funding from the Engineering and Physical Sciences Research Council for a centre for doctoral training in Mathematical Modelling, Analysis and Computation (MAC-MIGS) and more recently for a new centre for doctoral training in Algebra, Geometry and quantum fields (AGQ), in collaboration with the University of Glasgow. Many of the doctoral students work on topics in statistics
The International Centre for Mathematical Sciences (ICMS), located in the centre of Edinburgh, is another physical and networking resource for our staff. ICMS attracts top international mathematical visitors all year round through its extensive programme of international workshops, meetings, and other research and outreach activities. Many of
our staff spend a couple of days a week there, to meet with collaborators at the University of Edinburgh.
The School of Mathematical and Computer Sciences has an Athena SWAN Silver Award and is committed to its equality charter, which includes having a diverse and inclusive workforce, and to offering equality of opportunity to all.
Key Duties and Responsibilities
The post-holder will be required to:
Lead, carry out and publish internationally excellent research in applied statistics, actuarial data science or statistical data science, or a related field; Apply for research funding through either the submission of high-quality grant proposals or funding from industry, with the goal of building a research group; Undertake knowledge exchange activities to promote and disseminate your research; Carry out such administrative and recruitment activities as may be required to achieve these aims; Develop and deliver innovative teaching in statistics, actuarial science and related fields at undergraduate and postgraduate level; Be responsible to the Head of Department for performing the activities listed above in a way that will maintain and enhance the School’s reputation for excellence.
The successful candidate will be based at our Edinburgh campus in the UK. We encourage applications from under-represented groups. We welcome requests for flexible working arrangements and normally accommodate them.
Education, Qualifications and Experience
As a successful candidate, you will lead, carry out and publish internationally excellent research in your field. You will have a strong track record of research in applied statistics or actuarial data science - which may also include machine learning, financial risk and climate change risk - as demonstrated through publications, citations, external invitations and research funding. You will be established as an international research leader, with the ambition to build a world-class academic group and have the experience or potential to supervise PhD students and post-doctoral researchers.
You will have the relevant experience to engage in and innovate our specialised actuarial, statistical, data science and financial degree programmes. You will have the drive and commitment to contribute to the expansion of our successful postgraduate programmes.
Essential Criteria
PhD in statistics or statistical data science or actuarial science, or a related field. Track-record of internationally-leading research in the areas of applied statistics or actuarial data science with internationally excellent publications. Demonstrable teaching experience related to courses in the Department, as well as skills to supervise undergraduate and postgraduate dissertations. Excellent interpersonal and teamwork skills. Potential, ambition and plans to obtain research funding. Ability to supervise successfully PhD students.
Desirable Criteria
Track record of obtaining research funding. Track record of successful supervision of PhD students and/or post-doctoral researchers. Experience of statistical or actuarial work with industrial partners. Potential to provide leadership in the development and implementation of research strategy and in the planning, organisation and development of learning and teaching activities in the Department.
