ORGANISATION/COMPANYUniversity of Durham
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE21/06/2017 12:00 - Europe/Athens
LOCATIONUnited Kingdom › Durham
TYPE OF CONTRACTTemporary
HOURS PER WEEK35
EU RESEARCH FRAMEWORK PROGRAMMEH2020
Reference Number: 005509
Post: UTOPIAE Early Stage Researcher (Marie Curie)
Department: Department of Mathematical Sciences
Location: Durham City
Contract Type: Full Time & Fixed Term (36 months)
Grade: Marie Curie – See salary information below
Opening Date: 18th May 2017
Closing Date: 21st June 2017
UTOPIAE ESN: ESR8 and ESR9
Frank Coolen, Department of Mathematical Sciences, email@example.com
UTOPIAE: Uncertainty Treatment and Optimisation in Aerospace Engineering}
UTOPIAE is a training and research network (ETN) funded by the European Commission through the H2020 funding stream. The main objectives of this research programme are: To train, by research and by example, 15 Early Stage Researchers (ESR) in the field of Uncertainty Quantification and Optimisation and to become leading independent researchers and entrepreneurs that will increase the innovation capacity of the EU, and to equip them with the skills needed for successful careers in academia and industry; to develop, through the ESRs individual projects, fundamental mathematical methods and algorithms to bridge the gap between Uncertainty Quantification and Optimisation and between Probability Theory and Imprecise Probability Theory for Uncertainty Quantification; and to efficiently solve high-dimensional, expensive and complex engineering problems. Details about the UTOPIAE ETN are available from www.utopiae.eu .
The Department of Mathematical Sciences at Durham University (United Kingdom) participates in UTOPIAE and will host two ESRs (projects ESR8 and ESR9). Within the UTOPIAE ETN, we have a leading role and responsibility on exploration and development of Imprecise Probability theory and methods. The Durham team is led by Prof. Frank Coolen (also supervisor for ESR8) and includes Dr Louis Aslett (supervisor ESR8), Dr Jochen Einbeck (supervisor ESR9) and Dr Matthias Troffaes (supervisor ESR9).
For these two positions we will be looking to appoint talented and well-prepared Early Stage Researchers, in line with the EU rules for such a position. These are mainly: (1) not yet having completed PhD studies; (2) not more than 4 years research experience; (3) applicants cannot stay in the country they have resided in for more than 12 months during the past 3 years, so most likely this means `non-UK' applicants (this to encourage mobility throughout the EU). These will be Researcher positions, as members of staff of the university for 3 years starting October 2017, where the researchers will also register for PhD studies to be completed in the same time frame.
- ESR8: Prediction of System Reliability during Design Phases
Objectives: To develop suitable theory of system reliability quantification, using imprecise probabilities, in order to reflect carefully the uncertainties involved in the design processes in aerospace engineering at different stages; To derive an approximation of the lower and upper probabilities of system functionalities; To upscale to the propagation of upper and lower previsions to large systems; To study a representation of uncertainty in multi-phased design of aerospace systems.
Expected Results: A theoretical and computational framework for system reliability quantification in multi-phase processes using Imprecise Probability theory. A theoretical and computational framework for robust optimisation and decision making in multi-phase processes. A demonstrative example of application to the life cycle assessment of a launcher. New methods for system reliability quantification at different stages of system design, reflecting indeterminacy in the specification of the required functionality and providing the opportunity to focus on robustness with regard to resilience of the system. New computational methods, including the use of approximations, to enable upscaling of recently presented theory of imprecise probabilities for system reliability to large real-world multi-phase processes.
Planned Secondments: Strathclyde University (Glasgow, UK; about April - June 2019) to work on the application of imprecise probabilities and expert elicitation to the end-to-end design of space systems. ESTECO (Trieste, Italy; about January - March 2020) to work on the application of the newly developed methodology to multidisciplinary model-based collaborative system engineering.
- ESR9: Large Scale Simulation for Quantifying Severe Uncertainty
Objectives: This project is concerned with statistical inference for highly dimensional data with limited structural knowledge. The specific character of such situations would be (i) the data structure is too complex to describe the data through parametric models (ii) the dimension is too high too describe the data through nonparametric or sufficiently flexible semiparametric models (iii) even if either (i) or (ii) was feasible, there is considerable uncertainty on the type of structure and interaction which the data to be modelled exhibit; partly due to overwhelming complexity or lack of data.
This project will take a unified Bayesian-frequentist viewpoint, employing adequate regularization techniques which aim at sparse model representations through appropriate priors or penalties, respectively. To quantify the uncertainty of the resulting estimates, methods from imprecise probability will be investigated, which can be considered as the natural cutpoint between the Bayesian and the frequentist paradigm. In this context, we will investigate how standard statistical simulation approaches, such as for instance Markov chain Monte Carlo, can be extended to do inference from highly dimensional data, in a way that leads to computationally efficient yet still reliable inference about the actual risks in the system; to derive theoretical results from small scale tests; to upscale the dimensionality of the application, depending on the results of the small scale tests.
Expected Results: Enabling methods of robust and non-parametric character to be applied to much larger problems than is currently possible. An efficient computational framework to deal with highly dimensional data with limited structural knowledge. New efficient statistical simulation techniques. Improved representation of model uncertainty in simulation models, leading to better risk-informed decisions.
Planned Secondments: National Physical Laboratory (Teddington, UK; about August - October 2018) to work on the treatment of experimental data and model validation. Von Karman Institute (Sint-Genesius-Rode, Belgium; about April - June 2019) to work on high-dimensional uncertainty propagation and the treatment of experimental data.
Salary and Gross Living Allowance:
3072,68 Euro per month living allowance, + 600 Euro per month mobility allowance, + 500 Euro per month family allowance (if relevant). These amounts are gross amounts, subject to taxation according to each host institution national law. Consequently, the net salary results from deducting all compulsory (employer/employee) social security contributions as well as direct taxes (e.g. income tax) and insurance from these gross amounts.
- Early Stage Researchers (ESR) shall, at the date of recruitment (see below) by the host organisation, be in the first four years (full-time equivalent research experience) of their research careers (i.e. past Master degree or equivalent) and have not been awarded a doctoral (PhD) degree.
- Date of Recruitment normally means the first day of the employment of the ESR for the purposes of this project (i.e. the starting date indicated in the employment contract or equivalent direct contract).
- Full Time Equivalent Research Experience is measured from the date when a researcher obtained the degree which would formally entitle him/her to embark on a doctorate, either in the country in which the degree was obtained or in the country in which the researcher is recruited or seconded, irrespective of whether or not a doctorate is or was ever envisaged.
- Mobility Rule: at the time of recruitment by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organisation for more than 12 months in the 3 years immediately prior to the reference date. Compulsory national service and/or short stays such as holidays are not taken into account.
- At the starting time of the positions, the candidates must have completed the courses that would have allowed them to enrol in a doctorate program either in the country where they are studying or in the country offering the position.
- Gross living allowance / related allowances are subject to employment laws and compulsory employer and employee costs deduction.
General information about the UTOPIAE ETN is available from www.utopiae.eu . Information about the Department of Mathematical Sciences at Durham University is available from www.dur.ac.uk/mathematical.sciences/ . For further information about the overall contribution from Durham to UTOPIAE, or specific information about ESR8, please contact Prof Frank Coolen (firstname.lastname@example.org). For specific information about ESR9 please contact Dr Jochen Einbeck (email@example.com).
- Successful candidates must satisfy the eligibility criteria (see above).
- An excellent academic record in Statistics, Mathematics, Engineering or related area, including achievement of (or in the process of achieving) a Masters Degree in one of these areas, and a first class (or equivalent) Bachelor degree (or equivalent) in one of these areas.
- Demonstrable experience in mathematical or statistical programming.
- Enthusiasm and confidence about the UTOPIAE project, in particular about Uncertainty Quantification with the use of Imprecise Probabilities and the application area of Aerospace Engineering. Successful candidates agree to participate actively in all training and research events organised as part of the UTOPIAE project.
- Ability to work well both individually and as part of a team.
- Excellent English language skills.
- Experience with Imprecise Probabilities or Aerospace Engineering.
- Experience with software development and algorithm design.
- Scientific publications in Statistics, Mathematics, Engineering or related area.
EURAXESS offer ID: 193373