www.acad.jobs : academic jobs worldwide – and the best jobs in industry
                
     
Position: Research Associate in Risk Modelling for Digital Twins
Institution: The Alan Turing Institute
Location: United Kingdom
Duties: 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
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
   
Text: 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 recruitment@turing.ac.uk . 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. In accordance with the Equality Act, we welcome applications from anyone who meets the specific criteria of the post regardless of age, disability, ethnicity, gender reassignment, marital or civil partnership status, pregnancy and maternity, religion or belief, sex and sexual orientation. We are committed to building a diverse community and would like our leadership teal to reflect this. We therefore welcome applications from the broadest spectrum of backgrounds. Reasonable adjustments to the interview process will be made for any candidates with a disability. Please note all offers of employment are subject to obtaining and retaining the right to work in the UK and satisfactory pre-employment security screening which includes a DBS Check. Full details on the pre-employment screening process can be requested from HR@turing.ac.uk . Attachments Apply Already registered? Click here Email Password Password Recovery Not registered? Complete the form Apply with LinkedIn The operating system you are using causes the expiration of the uploaded files within one minute: we recommend you to upload the attachments as the last step before sending the application. Otherwise you will be asked to upload the files every 60 seconds. First Name Surname E-Mail Confirm E-Mail Cover Letter File Upload Click here (or drag and drop) to Upload a file pdf, doc, docx, xls, xlsx, ppt, pptx, odt, odp, ods, txt, rtf, jpg, jpeg, gif, png(Max: 2 MB) Add New Cover Letter Media Source Where did you see the advert? Select 80,000 Hours Academic positions Alan Turing Website CW Jobs Charity Jobs Data Scientist Jobs Design Jobs Board Diversity in Research Jobs Find a Postdoc.com Guardian Indeed Job Tensor JobBoard.net Jobs.ac.uk LinkedIn Marketing Week NLP People Nature Careers Other Praxis Auril Research Research Science HR Women in AI Women in Machine Learning and Data Science Women in data Women in tech Right to Work All appointments are subject to employees having the right to work in the UK to undertake the terms of their employment. In order to establish whether you have eligibility to work in the UK or will require sponsorship please answer the following questions. Are you a UK /European citizen? * Select No Yes Do you hold a valid permission (visa) to work in the UK? Select No Yes If you are not a UK Citizen If you answered 'yes' to the above question, are there any restrictions on the number of hours you may work? Select No Yes If there are restrictions, please provide details. Have you previously been sponsored by an employer to live and work in the UK? Select Deselect... No Yes If you are not a UK Citizen If you answered 'yes' to the above question, when did your sponsorship/visa lapse or end (please enter the date in the box to the right)? Personal Details Title Select Deselect... Dr. Miss Mr. Mrs. Ms. Mx. Prof. Sir. Known As Initial(s) Enter the initial(s) of your first and any middle name(s). Home Address Country*: Select... Afghanistan Albania Algeria American Samoa Andorra Angola Anguilla Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Brazil British Indian Ocean Territory British Virgin Islands Brunei Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Central African Republic Chad Chile China Christmas Cocos Islands Colombia Comoros Democratic Rep. of Congo (former Zaire) Cook Islands Costa Rica Croatia Cuba Cyprus Czech Rep. Denmark Djibouti Dominica Dominican Rep. East Timor Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands (or Malvinas) Faroe Islands Fiji Finland France French Guyana French Polynesia Gabon Gambia Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Isle of Man Israel Italy Ivory Coast Jamaica Japan Jersey Johnston Jordan Kazakhstan Kenya Kiribati Kosovo Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macau Macedonia Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Meeting Mexico Micronesia Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk North Korea Northern Marianas Norway Oman Pakistan Palau Palestinian Territory Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Islands Poland Portugal Puerto Rico Qatar Romania Russia Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Somalia South Africa South Korea Spain Sri Lanka Sudan Suriname Svalbard Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Vatican Venezuela Vietnam Virgin Islands Wallis and Futuna Western Sahara Yemen Zambia Zimbabwe Postcode*: Type a Postcode or a City and select a value from the list Locality: City*: Street: Flat / House Number: County: Region: Latitude: Longitude: Phone Mobile number Equal Opportunities Monitoring Form The Alan Turing Institute is committed to a policy of equal opportunities for its students, staff and applicants. In order to monitor the operation of this policy it is necessary to collect certain special categories of information from job applicants. The data collected here forms a confidential statistical record used solely for the purpose of monitoring the effectiveness of this policy. The information that you provide in this form is collected, maintained and stored securely in accordance with the General Data Protection Regulation and will only be shared with the HR team and the shortlisting panel involved in the recruitment process. Data used for statistical monitoring will be anonymised before being published outside of the HR Team. For information on how we use your special category data and how long we retain it for please refer to our recruitment privacy notice here: https://www.turing.ac.uk/recruitment-privacy-notice. The completion of this form is voluntary, but the information it contains helps us to better understand the composition of our organisation and examine our practices fully. All job applicants and employees will receive equal treatment regardless of race or ethnicity, sex, pregnancy and maternity, marriage and civil partnerships, religion or belief, disability, gender identity, sexual orientation and age. If you indicate a disability on this form, a member of our recruitment team may contact you to discuss reasonable adjustments we are able to offer. All personal information will be treated in accordance with the principles of the Data Protection Act (2018). Age Do you have any physical or mental health conditions or illnesses lasting or expected to last 12 months or more? Select Deselect... Yes No Prefer not to say Do you experience barriers or limitations in your day to day activities related to any disability, health conditions or impairments? Select Deselect... Yes No Prefer not to say Why do we ask this? Disability is a protected characteristic under the Equality Act 2010 and the two questions above help us understand the number of people in our community who face barriers and/or are disabled. What is your ethnic group? Choose one option that best describes your ethnic group or background. Select Deselect... Arab Asian or Asian British - Bangladeshi Asian or Asian British - Chinese Asian or Asian British - Indian Asian or Asian British - Pakistani Black or Black British - African Black or Black British - Caribbean Mixed - Asian and White Mixed - Black African and White Mixed - Black Caribbean and White White - English / Welsh / Scottish / Northern Irish / British White - Gypsy or Irish Traveller White - Irish White - Roma Any other Asian background Any other Black background Any other Mixed background Any other White background Any other Ethnic background Not known Prefer not to say If you selected 'Any other' for ethnicity, please describe below: What best describes your gender? Select Deselect... Man Non-binary Woman Prefer to self-describe/My gender is not described by these options Prefer not to say If you selected ‘Prefer to self describe’ for gender, please describe below: Caring responsibilities Select Deselect... None Primary or joint carer of a child or children (under 18) Primary or joint carer of a disabled child or children Primary or joint carer or assistant for a disabled adult (18 years or over) Primary or joint carer or assistant for an older person or people (65 and over) Secondary carer (another person carries out the main caring role) I have caring responsibilities but prefer not to specify what these are Prefer not to say Please let us know if you require any reasonable adjustments for the interview Select Deselect... I do require adjustments I don't require any adjustments Prefer not to say Rehabilitation of Offenders You must tell us if you have any criminal convictions or outstanding charges that are not spent under the terms of the Rehabilitation of Offenders Act 1974. This Act enables some criminal convictions to become 'spent', or ignored, after a 'rehabilitation period'. A rehabilitation period is a set length of time from the date of conviction. After this period, with certain exceptions, an ex-offender is not normally obliged to mention the conviction when applying for a job. Under the terms of the Act, a spent conviction is not proper grounds for not employing - or for dismissing - someone. Having a criminal conviction will not necessarily bar you from working for us and criminal convictions which are not relevant to the post being applied for will not be taken into account when selection decisions are being made Do you have any criminal convictions? Select No Yes if yes, please provide details. CV Click here (or drag and drop) to Upload a file doc, docx, txt, rtf, pdf, odt (Max: 2 MB) Choose from Dropbox Nome file The Alan Turing Data protection and submission declaration The Alan Turing Institute is committed to a policy of equal opportunities for its students, staff and applicants. In order to monitor the operation of this policy it is necessary to collect certain special categories of information from job applicants. The data collected here forms a confidential statistical record that we use for the purpose of monitoring the effectiveness of this policy. The information that you provide in this form is collected, maintained and stored securely in accordance with the UK General Data Protection Regulation and will only be shared with individuals who need to see it as part of their role and/or to the extent required by law. For example, in some cases, we may be required by law to carry out certain background checks, including right to work checks, in which case we may share some of your personal information with the appropriate background check providers in accordance with our legal obligations. Data used for statistical monitoring will be anonymised before being published outside of the HR Team. For information on how we use your special category data and how long we retain it for please refer to our recruitment privacy notice here . All personal information will be treated in accordance with the principles of the UK General Data Protection Regulation and Data Protection Act (2018). I declare that I have read and understood the information, and I understand that by making this declaration I am providing my consent for the Alan Turing Institute to share my personal information with background check providers to the extent required by law. (If you do not accept, your request cannot be processed) (Fields marked with * are required) Submit Powered by
Please click here, if the job didn't load correctly.







Please wait. You are being redirected to the job in 3 seconds.