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> On 12 Nov 2019, at 00:04, allstat automatic digest system <[log in to unmask]> wrote:
>
> There are 13 messages totaling 808 lines in this issue.
>
> Topics of the day:
>
> 1. S3RI seminar live stream: Matteo Fasiolo
> 2. JOB| Tenured or Tenure-Track Faculty Position in Business
> Statistics/Econometrics
> 3. JOB | Researcher and Intelligence Analyst, City of Westminster Council
> 4. JOB | Quantitative Researcher, Cambridge Assessment (2)
> 5. CFE-CMStatistics 2019, London 14-16 December: Last Call for Participation,
> Posters and Short Talks
> 6. Maths/Stats Graduate Opportunity, based near Manchester/Macclesfield
> 7. PhD: Studentship in causal inference, University of Sheffield
> 8. Seminar: Edinburgh Statistics Seminars - Dr Iain L. MacDonald (University
> of Cape Town) - Fri 15th Nov
> 9. JOB: Statistician, Centre for Cancer Prevention, Queen Mary University of
> London
> 10. JOB reminder: Research Associate/Assistant, University of Leicester, UK
> 11. PhD: University of Edinburgh, studentship in uncertainty quantification
> for landscape decisions
> 12. JOB: Bicentennial Fellowship in Actuarial Science, Heriot-Watt University
>
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> ----------------------------------------------------------------------
>
> Date: Mon, 11 Nov 2019 08:20:50 +0000
> From: "Ogden H.E." <[log in to unmask]>
> Subject: S3RI seminar live stream: Matteo Fasiolo
>
> The Southampton Statistical Sciences Research Institute presents:
>
> Dr Matteo Fasiolo, University of Bristol
>
> on
>
> Calibrated additive quantile regression for short-term electricity demand forecasting
>
> Thursday, 14 November, 2-3pm
>
> A live web-cast will be available at
> https://southampton.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=87cc7058-7742-472a-a423-ab020087d032
>
> Full details at
> https://calendar.google.com/calendar/event?eid=NmNkNTAyanE1azVqb2Q2NjRlZ2l1bWpvOTdfMjAxOTExMTRUMTQwMDAwWiB2djRiaGljbDBmNzFlNm51OTRnb3FmN24wMEBn
>
> For information on future S3RI seminars, see https://tinyurl.com/s3riseminar
>
> You may leave the list at any time by sending the command
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 09:24:03 +0000
> From: "StatsJobs.com" <[log in to unmask]>
> Subject: JOB| Tenured or Tenure-Track Faculty Position in Business Statistics/Econometrics
>
> Tenured or Tenure-Track Faculty Position in Business Statistics/Econometrics, University of Alberta
>
> The University Of Alberta School Of Business invites applications for a full-time tenured or tenure-track faculty position in Statistics/Econometrics with an emphasis on business analytics. Demonstrated interest in Management Information Systems or Operations Management will be considered an asset. The anticipated start date is July 1, 2020.
>
> Candidates will have graduated from an accredited PhD program in a relevant area, such as Statistics, Econometrics, or Operations Research. Candidates who are close to PhD completion may be considered; however, the appointment will be contingent upon the completion of the PhD by an agreed-upon date. It will be considered an asset if candidates possess an excellent research record or have the potential to publish in top journals in Statistics/Econometrics, have an alignment with the current research competencies of the department (high dimensional statistics or time series), and have shown evidence of teaching excellence. Candidate applicants will have a proven track record of (or demonstrated interest in) institution building and service in addition to exceptional scholarship in Statistics/Econometrics. Proficiency in English is required.
>
> Responsibilities of the position include teaching Statistics/Management Science courses in undergraduate and graduate programs, conducting and publishing research in top tier Statistics/Econometrics journals, and service to the School’s academic activities. The Alberta School of Business has an energetic PhD program and the successful candidate will be expected to play an active role in its continuing success and development.
>
> More Information >>>>> http://bit.ly/36Vgvoz
>
> View Similar Jobs >>>>> www.StatsJobs.com
>
>
> .
>
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 09:30:23 +0000
> From: "StatsJobs.com" <[log in to unmask]>
> Subject: JOB | Researcher and Intelligence Analyst, City of Westminster Council
>
> Researcher and Intelligence Analyst, City of Westminster Council
>
> Boasting a 24/7 nightlife, iconic shopping destinations such as Carnaby Street and famous tourist attractions including Buckingham Palace, Westminster is one of the most alluring places in which to live, work and visit. Made up of a diverse range of multicultural neighbourhoods that span the elegance of Knightsbridge and the quirky charms of Soho, we witness more than 1million people passing through the area every day – so our role in our communities’ lives is of vital importance.
>
> The Role:
>
> Our dynamic team covers a huge scope of fascinating topics and analysis methods, and it is here that you could join us. We're currently adopting an exciting new City for All strategy – where you will play an integral role in converting insights into compelling outputs that will help us connect to our audiences and create impact. The challenge of using research to influence behaviour change – plus other projects relating to local government policy – will provide an array of creative challenges in which you will assist the strategic direction of council services by anticipating issues and finding practical solutions. Working with our academic partners, your multi-method analysis will result in targeted campaigns and measurement of impact.
>
> More Information >>>>> http://bit.ly/36R0Zdv
>
> View Similar Jobs >>>>> www.StatsJobs.com
>
>
> .
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 09:50:28 +0000
> From: Tom Benton <[log in to unmask]>
> Subject: JOB | Quantitative Researcher, Cambridge Assessment
>
> Job Title: Research Officer
> Contract: Fixed Term until November 2020
> Salary: £26,000 - £36,500
> Location: Cambridge
>
> What it’s about:
>
> The Research Division conducts and publishes authoritative research in order to validate, improve and develop Cambridge Assessment’s products and services, and to influence thinking and policy on educational assessment. We research a wide range of assessment issues working with colleagues across the Group to provide a sound evidence base.
>
> This particular job is about applying your quantitative research skills to help ensure that the tests, examinations and other forms of assessment offered by Cambridge Assessment are reliable, useful and fair. For example, this may include research into the on-going issues of how to ensure that examinations remain equally difficult over time, how to ensure the accuracy of marking, and understanding the impact of policy changes upon students. In addition, your work will contribute to knowledge in the assessment field more widely.
>
> What we’re looking for:
>
> Qualifications
>
> Postgraduate qualification in statistics, research methods or another discipline with a substantial quantitative research element.
>
> Skills and behaviours
>
> Practical skills in data analysis including necessary programming skills (ideally using SAS or R)
> Good understanding of statistical methods
> Ability to communicate clearly in written reports and oral presentations.
> Ability to write research papers and reports of publishable quality
>
> Who we are
>
> Cambridge Assessment is Europe's largest assessment group, incorporating three major awarding bodies. It plays a leading role in researching, developing and delivering assessment to eight million candidates in 170 countries every year. The Group is a department of the University of Cambridge and a not-for-profit organisation.
>
> For more information and application instructions go to
> https://careers.cambridgeassessment.org.uk/job/Cambridge-Research-Officer/566623101/
>
> You may leave the list at any time by sending the command
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 09:58:02 +0000
> From: Tom Benton <[log in to unmask]>
> Subject: JOB | Quantitative Researcher, Cambridge Assessment
>
> Job Title: Research Officer
> Contract: Fixed Term until November 2020
> Salary: £26,000 - £36,500
> Location: Cambridge
>
> What it's about:
>
> The Research Division conducts and publishes authoritative research in order to validate, improve and develop Cambridge Assessment's products and services, and to influence thinking and policy on educational assessment. We research a wide range of assessment issues working with colleagues across the Group to provide a sound evidence base.
>
> This particular job is about applying your quantitative research skills to help ensure that the tests, examinations and other forms of assessment offered by Cambridge Assessment are reliable, useful and fair. For example, this may include research into the on-going issues of how to ensure that examinations remain equally difficult over time, how to ensure the accuracy of marking, and understanding the impact of policy changes upon students. In addition, your work will contribute to knowledge in the assessment field more widely.
>
> What we're looking for:
>
> Qualifications
> Postgraduate qualification in statistics, research methods or another discipline with a substantial quantitative research element.
>
> Skills and behaviours
> Practical skills in data analysis including necessary programming skills (ideally using SAS or R)
> Good understanding of statistical methods
> Ability to communicate clearly in written reports and oral presentations.
> Ability to write research papers and reports of publishable quality
>
> Who we are:
>
> Cambridge Assessment is Europe's largest assessment group, incorporating three major awarding bodies. It plays a leading role in researching, developing and delivering assessment to eight million candidates in 170 countries every year. The Group is a department of the University of Cambridge and a not-for-profit organisation.
>
> For more information and application instructions go to https://careers.cambridgeassessment.org.uk/job/Cambridge-Research-Officer/566623101/
>
>
> Any dissemination or copying of this email or attachments is strictly prohibited unless you are the intended recipient or are responsible for delivering the message to the intended recipient. If you have received this email in error, please let us know and then delete the original emails and any attachments. Emails are not secure and therefore Cambridge Assessment and OCR (Oxford Cambridge and RSA Examinations is a company limited by guarantee, registered in England. Registered office: 1 Hills Road, Cambridge CB1 2EU. Company number: 3484466 and an exempt charity) do not accept legal responsibility for the contents of this message. Any views or opinions presented are solely those of the author and do not necessarily represent those of Cambridge Assessment or OCR unless specifically stated. The information contained in this email may be subject to public disclosure under the Freedom of Information Act 2000 and unless legally exempt from disclosure, the confidentiality of this email and your reply cannot be guaranteed.
>
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 10:19:59 +0000
> From: Erricos Kontoghiorghes <[log in to unmask]>
> Subject: CFE-CMStatistics 2019, London 14-16 December: Last Call for Participation, Posters and Short Talks
>
> 13th International Conference on
> Computational and Financial Econometrics (CFE 2019)
> http://www.cfenetwork.org/CFE2019
> &
> 12th International Conference of the ERCIM WG on
> Computational and Methodological Statistics (CMStatistics 2019)
> http://cmstatistics.org/CMStatistics2019/
>
> 14-16 December 2019, Senate House University of London, UK
>
> Posters and selected short talks will still be considered until Friday 15th of November:
> CFE: http://cfenetwork.org/CFE2019/submission.php
> CMStatistics: http://cmstatistics.org/CMStatistics2019/submission.php
>
> The programme and list of participants are available at
> http://www.cmstatistics.org/CMStatistics2019/programme.php
>
> The joint programme is composed of about 430 sessions comprising over 1700 abstracts.
>
> Keynote Speakers:
> o David van Dyk, Imperial College London, UK.
> o Hashem Pesaran, University of Southern California, USA.
> o Sofia Olhede, EPFL, Switzerland.
> o Peter Winker, University of Giessen, Germany.
> o Liudas Giraitis, Queen Mary University of London, UK.
>
> Co-Chairs:
> CMStatistics: Jochen Einbeck, Michael Daniels, Chenlei Leng, Peter Rousseeuw, Grace Yi.
> CFE: Josu Arteche, Walter Distaso, Roxana Halbleib, Mathieu Rosenbaum.
>
> Tutorials on R Programming and mixture models, with application to image analysis will be given by Jochen Einbeck.
>
> Important dates:
> Late registration: 22 November 2019
> Tutorials: 13 December 2019
> Conference: 14-16 December 2019
>
> Main sponsors:
> Journal of "Econometrics and Statistics", Elsevier
> http://www.elsevier.com/locate/ecosta
> Journal of "Computational Statistics & Data Analysis", Elsevier
> http://www.elsevier.com/locate/csda
>
> For further information please contact: [log in to unmask]
>
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 10:24:37 +0000
> From: James Pike <[log in to unmask]>
> Subject: Maths/Stats Graduate Opportunity, based near Manchester/Macclesfield
>
> Adelphi Real World are recruiting statistical analysts to join an existing team of analysts.
>
> Company:
> Adelphi Real World conducts international market research surveys, and bespoke studies, for pharmaceutical companies. We are based in Bollington, close to Macclesfield, about 15 miles south of Manchester.
>
> Job:
> We deliver a wide range of statistical output to our clients - descriptive statistics, regression modelling, propensity score techniques, survival analysis, health outcomes, health economic modelling, etc.
>
> Candidate:
> Candidates should hold, or be about to hold, a good honours degree (2:1 or 1st) in mathematics and/or statistics.
>
> Excellent communication skills are essential as the role will demand interaction with other team members and clients.
> Benefits include a generous holiday allowance, private health care, life insurance, membership of an onsite gym, a contributory pension scheme and a bonus scheme (eligibility for the bonus scheme is after a year's service).
>
> Starting salary is £22K.
>
> Applications:
> Please send CVs with a brief email to [log in to unmask]<mailto:[log in to unmask]>
>
> James Pike
> Senior Statistical Scientist
>
> DISCLAIMER: The information in this message is confidential and may be legally privileged. It is intended solely for the addressee. Access to this message by anyone else is unauthorised. If you are not the intended recipient, any disclosure, copying, or distribution of the message, or any action or omission taken by you in reliance on it, is prohibited and may be unlawful. Please immediately contact the sender if you have received this message in error.
>
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 14:03:31 +0000
> From: Nicholas R Latimer <[log in to unmask]>
> Subject: PhD: Studentship in causal inference, University of Sheffield
>
> Applications are open for a PhD Studentship in causal inference methods for
> the analysis of cancer registry data.
>
> Location: University of Sheffield
>
> Start date: September 2020 (latest)
>
> Application deadline: 30th November 2019
>
> The PhD is based in the School of Health and Related Research (ScHARR),
> University of Sheffield, and is funded by Yorkshire Cancer Research and
> BresMed Health Solutions Ltd. Fees will be paid, plus an annual maintenance
> grant and a training budget. Broadly, the project will be to do with causal
> inference in the context of cancer data and health technology assessment.
> In particular, the project could focus on causal inference to estimate
> comparative effectiveness using UK cancer registry datasets.
>
> Prospective students are free to suggest their own research plan, as long
> as it is in the broad area of causal inference and health technology
> assessment.
>
> Advert is here:
> https://www.findaphd.com/phds/project/phd-studentship-in-causal-inference-for-the-analysis-of-cancer-registry-data/?p105476
>
>
> Supervision will be by Dr Nicholas Latimer and others, depending upon the
> topic chosen. For further details, please contact [log in to unmask]
>
> --
> --------------------------------------------------------------------
> ***Fully funded PhD studentship on causal inference:
> https://www.findaphd.com/phds/project/phd-studentship-in-causal-inference-for-the-analysis-of-cancer-registry-data/?p105476
> ***
>
> Nicholas Latimer, PhD
> Reader in Health Economics
> Yorkshire Cancer Research Senior Fellow
>
> Health Economics and Decision Science
> ScHARR
> University of Sheffield
> Regent Court
> 30 Regent Street
> Sheffield
> S1 4DA
> Tel: +44 (0) 114 222 0821
> Fax:+44 (0) 114 272 4095
> Email: [log in to unmask]
> www.shef.ac.uk/heds
>
> Follow HEDS at :http://scharrheds.blogspot.co.uk/
> Twitter: @NRLatimer
>
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>
> ------------------------------
>
> Date: Mon, 11 Nov 2019 14:07:19 +0000
> From: Serveh Sharifi <[log in to unmask]>
> Subject: Seminar: Edinburgh Statistics Seminars - Dr Iain L. MacDonald (University of Cape Town) - Fri 15th Nov
>
> Speaker: Dr Iain L. MacDonald (University of Cape Town)
>
> Title: Is EM really necessary here? Some examples where EM seems over-elaborate
>
> Date and time: Fri 15 Nov 2019, 15:05 - 16:00
>
> Location: JCMB - Room 5328
> https://www.maths.ed.ac.uk/school-of-mathematics/contact/travel-directions
>
> Abstract: If one is to judge by counts of citations of the fundamental paper (Dempsteret al., 1977), EM algorithms are a runaway success. But it is surprisingly easy to find published applications of EM that are apparently unnecessary, in the sense that there are simpler methods available that will solve the relevant estimation problems. In particular, such problems can often be solved by the simple expedient of submitting the observed-data likelihood (or log-likelihood) to a general-purpose optimization routine. This can dispense with the need to derive and code (or modify) the E and M steps, a process which can sometimes be laborious or error-prone. Here I discuss five or six such applications of EM in some detail, and describe briefly some others that have already appeared in the literature. In all these cases, there seems to be no good reason to choose EM. Whether these are atypical of applications of EM is not obvious. But it is clear that there are problems traditionally solved by EM (e.g. the fitting of mixtures of normals or Poissons) that are easy to solve by other means. It is suggested that, before going to the effort of devising an EM algorithm to use on a new problem, the researcher should consider whether other methods (e.g. direct numerical maximization or an MM algorithm of some other kind) may be either simpler to implement or more efficient.
>
> References: Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm (with discussion). Journal of the Royal Statistical Society Series B,39, 1–38.
>
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> ------------------------------
>
> Date: Mon, 11 Nov 2019 14:26:01 +0000
> From: Rhian Gabe <[log in to unmask]>
> Subject: JOB: Statistician, Centre for Cancer Prevention, Queen Mary University of London
>
> Job: Statistician
> Department: Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine
> Grade 5: £38,084-£44,807 per annum, inclusive of London Allowance.
> Reference: QMUL20554
> Closing date: 10-Dec-2019
>
> Link: https://webapps2.is.qmul.ac.uk/jobs/job.action?jobID=4825
>
> Applications are invited for a Statistician to support trials at Centre for Cancer Prevention, part of Barts Clinical Trials Unit. The centre is at the forefront of international research into the prevention and control of cancer. We have particularly active research programmes in breast, endometrial, cervical, colorectal, lung and prostate cancer prevention, cancer screening and statistical methods for clinical trials and epidemiology.
>
> While the candidate will have the opportunity to be involved in other activities within the Centre, the main role is to undertake statistical analyses of studies investigating methods used to screen for and detect lung cancer.
>
> Applicants must have an MSc or PhD in Statistics or related quantitative field, experience of clinical trials and/or epidemiology, experience of using statistical analysis packages such as Stata, and excellent communications skills. Experience of working with large data sets would be a particular advantage. Please indicate in your covering letter how your experience matches the corresponding job profile (available as part of the online application process or through informal enquires).
>
> The post is a full time, fixed term appointment for two years. This post will be appointed at Statistician Grade 5 level, with a starting salary in the range of £38,084-£44,807 per annum, inclusive of London Allowance. Benefits include 30 days’ annual leave, a staff pension scheme and an interest-free season ticket loan.
>
> Informal enquiries should be addressed to Professor Rhian Gabe at [log in to unmask]
>
> You may leave the list at any time by sending the command
>
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>
> ------------------------------
>
> Date: Mon, 11 Nov 2019 15:42:08 +0000
> From: "Bujkiewicz, Sylwia I. (Dr.)" <[log in to unmask]>
> Subject: JOB reminder: Research Associate/Assistant, University of Leicester, UK
>
> Research Assistant or Research Associate
>
> University of Leicester, Leicester, UK
>
> Biostatistics Research Group
>
> Department of Health Sciences
>
> Vacancy terms:
> Full-time open ended contract subject to fixed term funding.
> Funding is available until 31 December 2021
>
> Salary details:
> Grade 6 £28,331 - £32,817 per annum
> Grade 7 £34,804 - £40,322 per annum
>
> Advert closes midnight on:
> 15 Nov 2019
>
> We are looking for a Research Associate or Research Assistant to join the Biostatistics Research Group in the department of Health Sciences.
>
> The role will involve carrying out research, contributing as a team member to the MRC-funded project on "Inferring relative treatment effects from combined randomised and observational data", based within the Biostatistics Research Group in the Department of Health Sciences at the University of Leicester and in collaboration with colleagues at the Universities of Bristol and York. As a Research Associate your research will be independent and as a Research Assistant your research will be supervised.
>
> The post will involve the development and application of statistical methods as well as guidance on different ways in which observational evidence can be used in decision making in a Health Technology Assessment (HTA) context. This methodological development will be carried out within several work-packages using a series of real-world case studies to illustrate these.
>
>
> Research Assistant:
>
> you will be educated to MSc level in Biostatistics/Medical Statistics, Applied Statistics/Statistics, Epidemiology, Health Technology Assessment or a closely related area and have excellent communication skills.
> You will have experience in one or more of:
> · Biostatistics/Medical Statistics/Applied Statistics/Epidemiology/Health Technology Assessment/Operational Research
> · analysis of RCT and observational patient level data
> · simulation-based methods (including Markov Chain Monte Carlo)
> · meta-analysis/evidence synthesis methods (including network meta-analysis)
>
>
> Research Associate:
>
> you will be educated to PhD level (or relevant MSc plus research experience) in Biostatistics/Medical Statistics, Applied Statistics/Statistics, Epidemiology, Health Technology Assessment, Health Economics or a closely related area. You will also have outstanding communication skills, and a proven ability to contribute to the development of presentations and peer reviewed publications.
> You will have high-level expertise in one or more of:
> · Biostatistics/Medical Statistics/Applied Statistics/Epidemiology/Health Technology Assessment/Operational Research/Health Economics
> · analysis of RCT and observational patient level data
> · simulation-based methods (including Markov Chain Monte Carlo)
> · meta-analysis/evidence synthesis methods (including network meta-analysis)
>
>
> Informal enquiries are welcome and should be made to one of the following:
>
>
> Prof Keith R Abrams on [log in to unmask], +44 (0)116 229 7266,
>
> Dr Sylwia Bujkiewicz on [log in to unmask], +44 (0)116 229 7258,
>
> Prof Laura Gray on [log in to unmask], +44 (0)116 252 5491 or +44 (0)116 258 4043
>
> Prof Nuala Sheehan on [log in to unmask], +44 (0)116 229 7271,
>
> Prof Alex Sutton on [log in to unmask], +44 (0)116 229 7268.
>
> For more information and details how to apply visit:
>
> https://jobs.le.ac.uk/vacancies/vacancy-details.aspx?VacancyID=1006
>
> You may leave the list at any time by sending the command
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>
> ------------------------------
>
> Date: Mon, 11 Nov 2019 16:56:20 +0000
> From: Amy Wilson <[log in to unmask]>
> Subject: PhD: University of Edinburgh, studentship in uncertainty quantification for landscape decisions
>
> Applications are open for a PhD studentship in uncertainty quantification
> for UK landscape models.
>
> *Title:* Shaping the future of the UK’s landscapes – building a decision
> support system for sustainability
>
> *Location:* University of Edinburgh
>
> *Deadline:* 9 January 2020
>
> This project will develop a decision-support system to guide UK land use to
> a sustainable future by scaling a model of ecosystem processes and earth
> observation data into a national integrated system.
>
> The landscapes of the UK serve varied functions – e.g. supporting farmers’
> yields, forestry, biodiversity and recreation. For the future, there are
> several major questions. What should determine the nature of our landscapes
> in coming decades? How can landscapes be resilient to climate change and
> be supported sustainably? There are major challenges to building a system
> that can inform us in detail about these questions but there are also major
> opportunities with new data infrastructure, high resolution earth
> observation data, and powerful analytical tools and models.
>
> Currently, we can analyse and model land use either at national scale at
> coarse resolution, or at high resolution on a small scale. Fine-scale
> pattern is important in driving land use decisions, but a national system
> is critical for policy makers. The challenge here is to develop tools and
> algorithms that can scale between field and UK, to bridge the
> scale/resolution trade-off that currently limits decision support.
>
> This project is part of the Edinburgh Earth, Ecology and Environment
> Doctoral Training Partnership (E4 DTP), led by the School of GeoSciences at
> the University of Edinburgh. For more details see:
>
> https://www.ed.ac.uk/e4-dtp/how-to-apply/our-projects?item=829
>
> To apply and to see the eligibility criteria, see
> www.ed.ac.uk/e4-dtp/how-to-apply
>
> You may leave the list at any time by sending the command
>
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>
> ------------------------------
>
> Date: Mon, 11 Nov 2019 16:47:25 +0000
> From: "Clancy, Damian" <[log in to unmask]>
> Subject: JOB: Bicentennial Fellowship in Actuarial Science, Heriot-Watt University
>
> Job ref: IRC24850
> Closing date: 10 Jan 2020
> Salary: £32,817–£40,322
> Location: Edinburgh
> Department: Actuarial Mathematics and Statistics
> Duration: 36 months fixed-term, tenure track
>
> Heriot-Watt University, The Times International University of the Year 2018, has established a reputation for world-class teaching and leading-edge, relevant research, which has made it one of the top UK universities for business and industry. To celebrate our 2021 bicentenary of pioneering research, the School of Mathematical and Computer Sciences welcomes applications for a Bicentennial Fellowship in the area of actuarial science or a related field. These 3-year tenure-track fellowships are intended to support candidates at the start of their independent academic careers. These positions have arisen as part of an ongoing strategic expansion of the Department.
>
> The School is internationally renowned in actuarial science, financial risk, applied probability and statistics through the world-leading research activities of its Department of Actuarial Mathematics and Statistics, where the post holder will be located. Areas of particular strength include longevity risk modelling and management, applications of data science in insurance, genetics and insurance, financial risk management in pensions, morbidity modelling, financial modelling, stochastic modelling and inference in epidemiology and the life sciences, and mathematical and computational imaging.
>
> The Department has long-established, global links with the Actuarial Profession, including the Directorship of the Actuarial Research Centre (ARC) – a ground breaking virtual network of actuarial researchers and partner organisations from around the world. Within Scotland we have excellent links to the financial services industry through the Scottish Financial Risk Academy (SFRA), a partnership between industry and Scottish academic institutions which has been led from Heriot-Watt since its establishment in 2010.
>
> As the successful candidate, you will hold a PhD in a relevant subject area. You will carry out and publish internationally excellent research in your field. You will have the potential to become established as an international research leader with a strong research record. You will have the enthusiasm and communication skills to be able to engage in our statistical data science, actuarial and financial mathematics teaching programmes. Training and mentoring support will be provided during the fellowship. It is expected that after a successful review at the end of the 3 years, the position will change into an Assistant
> Professorship position.
>
> For informal discussion about the position please contact Prof Damian Clancy (Head of Department), [log in to unmask] , or Prof Andrew Cairns, [log in to unmask]
>
> The Department has a strong collaborative ethos, which supports our many partnerships and the School’s Athena Swan Bronze award, and is committed to having a diverse and inclusive workforce, and to offering equality of opportunity to all. Embracing diversity at Heriot-Watt University means we can select from the broadest pool to find the best person for the job – we encourage you to apply.
>
> For more information about the role and to apply, please go to: https://www.hw.ac.uk/about/work/jobs/job_SVJDMjQ4NTA.htm
> ________________________________
>
> Heriot-Watt University is The Times & The Sunday Times International University of the Year 2018
>
> Founded in 1821, Heriot-Watt is a leader in ideas and solutions. With campuses and students across the entire globe we span the world, delivering innovation and educational excellence in business, engineering, design and the physical, social and life sciences. This email is generated from the Heriot-Watt University Group, which includes:
>
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> 2. Heriot- Watt Services Limited (Oriam), Scotland's national performance centre for sport. Heriot-Watt Services Limited is a private limited company registered is Scotland with registered number SC271030 and registered office at Research & Enterprise Services Heriot-Watt University, Riccarton, Edinburgh, EH14 4AS.
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> End of allstat Digest - 9 Nov 2019 to 11 Nov 2019 (#2019-283)
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