ORGANISATION/COMPANYUniversity of Novi Sad Faculty of Sciences
RESEARCH FIELDMathematics › Applied mathematics
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE31/12/2018 17:00 - Europe/Brussels
LOCATIONSerbia › Novi Sad
TYPE OF CONTRACTTemporary
HOURS PER WEEK40
OFFER STARTING DATE01/03/2019
EU RESEARCH FRAMEWORK PROGRAMMEH2020 / Marie Skłodowska-Curie Actions
REFERENCE NUMBERMSCA-ITN-EID 812912
MARIE CURIE GRANT AGREEMENT NUMBER812912
The BIGMATH Network
BIGMATH is an Innovative Training Network programme for highly motivated young scientists, where state-of-the-art research is combined with a comprehensive training programme. The network is funded by the European Community through the Horizon 2020 MSCA-ITN-EID Actions. The European Commission wants to make research careers more attractive to young people and therefore offers early-stage researchers (ESRs) the opportunity to improve their research skills, join established research teams and enhance their career prospects via the so-called Marie Curie Initial Training Networks. The scientific goal of BIGMATH is to address the major challenges that the Big Data era is posing to mathematical research, in particular in the areas of optimization, statistics, and large-scale linear algebra.
The ESRs will be trained both on cutting-edge research on targeted mathematical disciplines, and on a wide set of “soft skills” that will enable them to transfer effectively their knowledge to the productive world, thus fostering the European market to create innovation.
These abilities will result from a close partnership between the academy, providing the students with up-to-date training and scientific knowledge on targeted mathematical disciplines, and a group of industries, who will complete the competences of the ESRs by exposing them to a set of Big Data-related real industrial problems.
The BIGMATH network consists of 4 universities and of 7 industrial partners located in Italy, Portugal, The Netherlands and Serbia.
For more information on BIGMATH, please visit the website http://itn-bigmath.unimi.it/ .
The expected research within the PhD scholarship
Project title: Big data optimization for logistic and supply chain management (ESR7)
Quality control of high tech components is very stringent, with admissible out of specification production going towards below the 1 ppm (one in a million) to 1 ppb (one in a billion). This, in effect, means it is not enough to minimize process variations: faulty products will be caused by an unknown combination of events. Because of the low occurrence rate, this becomes impossible to study by experiment, and root cause finding has to be performed on the detailed analysis of the propagation of and interaction between process variations. The number of parameters and interactions and the stochastic nature of the underlying models make both the root cause finding itself and the mitigation by (non-linear) optimal control very big. An approach is a sparse tensor representation of the high dimensional space, which in itself is a challenging optimization problem. Although it is a challengingly big computational approach, recent advances in computational equipment have made it nearly feasible: a further reduction in complexity in e.g. sparsity, and performance of underlying optimization strategies are required. An even more data-driven problem is at the logistic end of the process. Logistic and supply chain planning from A to B in a realistic network, with many different intermediate actors, each one having their own incentives and objectives, results into a massively complex, heavily constrained and possibly non-convex optimization problem. The aim of this project is to improve the control and adaptability of production processes and of supply chain management, under uncertainty conditions of a large-scale set of (constrained) variables. To tackle the problem, ESR will develop innovative optimization algorithms that can cope with huge amount of data in real time, to be applied to a mathematical model defined in such way that all important factors are well identified and able to model rare but significant events.
18 months to Sioux-Lime (Eindhoven-The Netherlands), a consulting company.
This secondment will be split into:
- Period I: 5 months at the beginning of the PhD program;
Objectives: to get a deep understanding of the problems to be solved; to get used to the data format;
- Period II: 13 months at the end of 2nd and 3rd year of the program;
Objective: to develop industrial project-related research.
The recruited PhD student will perform her/his activity under the supervision of Prof. Natasa Krejic at University of Novi Sad Faculty of Sciences, Department of Mathematics and Informatics.
The recruited PhD student will be enrolled in the PhD programme in Mathematics. She/he will receive a Monthly Living Allowance plus a Mobility Allowance compliant with the applicable EU Marie Skłodowska-Curie Actions-ITN general conditions.
Student will be duly covered under the appropriate social security scheme. She/he will receive a Monthly Living Allowance plus a Mobility Allowance compliant with the applicable EU Marie Skłodowska-Curie Actions-ITN general conditions.
The recruited PhD student will participate in the network training activities and work placements at the schools and laboratories of the participating academic and industrial partners. In addition, the training programme of the recruited ESR will be supplemented by regular meetings and workshops within the BIGMATH International Training Network.
Eligible ESR candidates may be of any nationality but must not, at the time of recruitment, have resided or carried out their main activity (work, studies, etc.) in Serbia for more than 12 months in the last 3 years immediately prior to the recruitment date.
A common scoring system and interviews of the candidates will be used, respecting privacy and protection of the Applicant's data. Female candidates and candidates with disabilities are encouraged to apply.
The selection process is based on two steps:
1. Evaluation of the documents provided by the Applicant (Assessment of academic records) and preselection of up to 3 candidates as the short-listed candidates.
2. A modelling or data analysis problem will then be submitted to the short-listed candidates passing phase 1, and they will be requested to present their results one week later, during an interview by the selection committee, which will be organized remotely, via teleconference.
The selection committee will be composed of representatives from the University of Novi Sad, Technical University of Eindhoven and Sioux-Lime. The first phase (preselection) will be concluded and the results will be announced to the short-listed candidates by email by January 13, 2019.
The modelling problems will be assigned by email on January 14, 2019 and the interviews will take place on January 21, 2019.
The selection process will end up by January 31, 2019.
- List of Documents to provide:
- Application Form (see attachment)
- Letter of motivation (max. 1 page)
- Copies of degree and academic transcripts (with grades and rankings)
- Resumé of Master's thesis (max. 5 pages)
- Short CV including a publication list (if any)
- Two Recommendation letters from academics prepared according to the attached template. Candidates must indicate the academics’ contact details when applying.
- Copy of Passport ID page
Required documents must be uploaded as PDF documents and zipped into a unique single file (ZIP o RAR). The application must be sent, in a single email to the following email address: firstname.lastname@example.org
REQUIRED EDUCATION LEVELMathematics: Master Degree or equivalent
REQUIRED LANGUAGESENGLISH: Excellent
In order to apply for a position in the PhD programme, students must have a Master of Science Degree (or equivalent) from a foreign University. The suitability of the foreign academic qualifications in terms of content is appraised by the University of Novi Sad, through the Assessment Committee constituted for admission to each PhD programme, in compliance with the regulations in force in Serbia and in a country in which the academic qualification was issued, and the international treaties or agreements pertaining to the conferment of qualifications for the continuation of studies. ESR shall, at the time of recruitment, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree. Fulltime equivalent research experience is measured from the date when the researcher obtained the Master degree, Part-time research experience will be counted pro-rata.
The Candidates should hold an MSc Degree by the starting date of the fellowship,
in one of the following areas: Mathematics, Applied Mathematics, Statistics.
- Duration of the contract: 36 months.
- Salary and additional benefits are according to EU-standards for Marie Curie ESRs. Additional benefits are foreseen for mobility and family allowance (if applicable).
- The ESR is expected to work full-time on the project (40 hours/week).
- The ESR must complete at least 18 months of secondments to an industrial partner.
- The ESR must actively participate in the events organized by the BIGMATH
Consortium, such as training/network events as well as in regular yearly Outreach Activities targeting different audiences. Recruitment, selection and appointment of the ESR are in compliance with the European Charter for Researchers and a Code of Conduct for the Recruitment of Researchers (Charter & Code; https://euraxess.ec.europa.eu/jobs/charter).
- All BIGMATH partners commit themselves to provide equal opportunities for all prospective applicants.
- ESRs’ progress will be regularly monitored. Every year, the candidates and their work will be challenged and questioned. Failure in providing evidence of a regular and continuous commitment may result in the exclusion from the programme.
- Good collaborative and social skills and an open-minded attitude are highly desirable.
- Proficiency in the English language (including both written and oral fluency) is essential.
EURAXESS offer ID: 356821
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