Ph.D fellowship in Computational Engineering
Ph.D fellowship in Computational Engineering
University of Stavanger
The University of Stavanger (UiS) has about 12,000 students and 1,800 employees. We are the only Norwegian member of the European Consortium of Innovative Universities. The university has high ambitions. We will have an innovative and international profile, and will be a driving force in knowledge development and in the process of societal change. Together with our staff and students, we will challenge the well-known and explore the unknown.
The Department of Energy Resources is part of the Faculty of Science and Technology. The international academic staff conducts research related to energy resources, technology for improved oil recovery (IOR), decision analysis and geosciences. Study programs offer courses related to the exploration and utilization of petroleum and natural resources. The department focuses on internationalization, with development of study programs in English and high mobility among academic staff and students. The department contributes significantly to the research activities and leadership of The National IOR Centre of Norway, established by the Ministry of Petroleum and Energy. There are currently XX employees in the department including research fellows and postdocs.
The University of Stavanger invites applicants for a Ph.D fellowship in Computational Engineering at the Faculty of Science and Technology, Department of Energy Resources. The postition is vacant from fall 2020.
Subject area for the position is Multi-Stage Learning and Decision Making – "What is the Optimal Time to Invest in New Technology?"
This is a trainee position that will give promising researchers an opportunity for academic development leading to a doctoral degree.
The appointment is for three years with research duties exclusively.
Information about the project:
Companies are continuously struggling with uncertainty when contemplating investments on new technology. Given that corporate technology often cost tens or hundreds of millions of dollars, an optimal investment program could generate significant savings.
The objective of this project is to study how the uncertainty of the benefits of a technology can affect decisions related to the adoption of the technology and the information-gathering process that supports the decision on the investment. More specifically, the study requires the formulation of a dynamic programming model where, in each period, the consumer adopts or rejects a new technology or waits and gathers additional information about the benefits of a technology by observing a signal/proof of the technology’s benefit.
The technology’s actual benefit may be constant or changing stochastically over time. The structural properties of the model should be investigated. The key challenge is to develop an appropriate yet tractable model that describes the uncertain “learning” over time and to build a decision model that can efficiently contemplate the multiple scenarios and options that may arise.
The key research objectives of the position are the following:
- Develop and implement efficient and flexible optimization methods to identify the optimal decision sequence with the dynamic structure discussed above. The technology’s actual benefit may be constant or changing stochastically over time. After observing a signal, the company (or consumer) updates its distribution on benefits using Bayes’ rule. In this model, the dynamic programming state variable is a probability distribution that describes the company’s (or consumer’s) beliefs about the benefits of the technology.
- Investigate the structural properties of the model: When does one distribution on benefits lead to higher values than another? Similarly, when is one signal process better than another? How do changes in the assumptions affect companies, optimal policies, and the timing of adoption decisions?
The research requires strong quantitative skills and solid understanding of topics such as probability analysis, quantitative modeling, geostatistics and data analytics, robust optimization, programming as well as petroleum reservoir engineering and/or geosciences. Although some of these specific skills can be acquired as a part of the PhD study, demonstrated analytical skills are required.
We are looking for applicants with a strong academic background who have completed a five-year master degree (3+2) within one or more of the following: industrial or applied mathematics, decision analysis, data science or geostatistical data analytics, information technology including numerical analysis and programming, Industrial economics, operational research, geoscientist or engineer with solid skills and interests in quantitative modeling, preferably acquired recently; or possess corresponding qualifications that could provide a basis for successfully completing a doctorate.
To be eligible for admission to the doctoral programmes at the University of Stavanger both the grade for your master’s thesis and the weighted average grade of your master’s degree must individually be equivalent to or better than a B grade.
If you finish your education (masters degree) in the spring of 2020 you are also welcome to apply.
Applicants with an education from an institution with a different grade scale than A-F should attach a confirmed conversion scale that shows how the grades can be compared with the Norwegian A-F scale.
Emphasis is also placed on your:
- ability to develop and implement (program) mathematical models
- motivation and potential for research within the field
- ability to work independently and in a team, be innovative and creative
- ability to work structured and handle a heavy workload
- having a good command of both oral and written English
- varied duties in a large, exciting and socially important organisation
- an ambitious work community which is developing rapidly. We strive to include employees at all levels in strategic decisions and promote an informal atmosphere with a flat organisational structure
- salary in accordance with the State Salary Scale, l.pl 17.515, code 1017, NOK 479,600 gross per year with salary development according to seniority in the position
- automatic membership in the Norwegian Public Service Pension Fund, which provides favourable insurance- and retirement benefits
- favourable membership terms at a gym and at the SIS sports club at campus
- employment with an Inclusive Workplace organisation which is committed to reducing sick leave, increasing the proportion of employees with reduced working capacity, and increasing the number of professionally active seniors
- "Hjem-jobb-hjem" discounted public transport to and from work
- as an employee in Norway, you will have access to an optimal health service, as well as good pensions, generous maternity/paternity leave, and a competitive salary. Nursery places are guaranteed and reasonably priced
- relocation programme in event of moving to Norway, including support and language courses for spouses
The appointee will be based at the University of Stavanger, with the exception of a stay abroad at a relevant centre of research.
It is a prerequisite that the appointee has a residence which enables him or her to be present at/available to the academic community during ordinary working hours.
The University currently employs few female research fellows within this academic field, and women are therefore particularly encouraged to apply.
The position has been announced in both Norwegian and English. In the case of differences of meaning between the texts, the English text takes precedence.
More information on the position can be obtained from:
- Professor Reidar B. Bratvold, tel: +47 976 51 969, e-mail: [email protected]
Information about the appointment procedure can be obtained from HR advisor Margot A.Treen, tel: +47 51831419, e-mail: [email protected]
To apply for this position please follow the link "Apply for this job". Register your application and CV including relevant education and work experience. In your application letter you must show your research interests and motivation to apply for the position.
The following documents must be uploaded as attachments to your application in separate files:
- list of publications
- other documentation that you consider relevant
The documentation must be available in either a Scandinavian language or in English. If the total size of the attachments exceeds 30 MB, they must be compressed before upload. Information and documentation to be taken into account in the assessment must be submitted within the application dealine.
Please note that information on applicants may be published even if the applicant has requested not to be included in the official list of applicants - see Section 25 of the Freedom of Information Act.
UiS only considers applications and attachments registered in JobbNorge.