PhD scholarship in Operations Research: Acceleration Methods for Stochastic Optimization Problems – DTU Management

The Department of Technology, Management and Economics at DTU invites applications for a PhD student position on the topic of using AI to reduce stochastic problems. You will be responsible for developing new aggregation and scenario reduction methods in stochastic optimization, using AI.
The Department of Technology, Management and Economics at DTU invites applications for a PhD student position on the topic of using AI to reduce stochastic problems.

You will be responsible for developing new aggregation and scenario reduction methods in stochastic optimization, using AI. Furthermore, you should (together with the team) participate in the development of solvers for stochastic optimization problems and test the methods on real-life data.

As part of the PhD, you will be following advanced courses to extend your skills, implement and test algorithms, and learn to write scientific papers.

Research area and project description
In the ERC-funded project DECIDE we aim at developing a new generation of heuristic and exact methods for two-stage stochastic optimization problems. The goal is to be able to solve considerably larger problems than before, involving many scenarios for the future. We will use AI-based methods as part of the solution process to generate scenarios and guide the search.

Many strategic stochastic optimization problems cover a long-time horizon, with many low-level decision variables. This means that the problems become very difficult to solve as an optimization problem. In order to speed up the solution process, it has been proposed to use data aggregation or scenario reduction to reduce the size of the problem.

Data aggregation exploits the periodicity of many problems, to select shorter time series to represent the full-time horizon without losing too much information. On the other hand, scenario reduction eliminates scenarios that are similar to each other.

Both approaches make use of clustering in either the time dimension or in the scenario dimension. The results show a substantial speed-up in solution times with only a small decrease in solution quality.

The aim of the PhD project will be to investigate whether AI can be used to reduce stochastic problems, without losing solution quality. In particular, the interplay between data aggregation and scenario reduction should be investigated.

You will join a strong academic team at DTU Management’s Management Science division. Three PhD students and four Postdocs will work on the project, as well as several international experts in operations research.

The project is headed by Professor David Pisinger who has published several papers in the field and supervised more than 30 PhD students.

DECIDE is funded by the European Research Council (ERC-2022-ADG).

Responsibilities and qualifications
As part of the DECIDE project you will be working on developing next generation of tools for decision making under uncertainty. You must:

• Have experience in AI models (e.g. Variational Autoencoders, Normalized Flows, Generative Adversarial Networks)
• Have experience in developing fast algorithms for hard combinatorial optimisation problems.
• Have some knowledge about stochastic optimization.
• Have knowledge about implementation of metaheuristics.
• Be passionate about research and pushing the scientific frontiers.
• Have excellent programming skills.
• Have good collaboration skills.
• Be fluent in English, spoken as well as written.

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

It would be an advantage if you have taken some courses in stochastic optimization or advanced algorithms.

Assessment
The assessment of the applicants will be made by two representatives from DTU Management.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.

The period of employment is 3 years. Starting date is 1 October 2024 (or according to mutual agreement). The position is a full-time position.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Professor, David Pisinger (DTU), tel.: +45 4525 4555, email: [email protected].

You can read more about DTU Management at www.man.dtu.dk.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

Application procedure
Your complete online application must be submitted no later than 31 July 2024 at 23:59 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
• A research statement (2-3 pages) explaining your ideas and relevant literature.

Applicants not providing all the above material will not be considered.

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

About us
DTU Management conducts excellent research in the intersection between management, technology and economics. We develop solutions in close cooperation with companies and public authorities. Our research aims at strengthening welfare, productivity, and sustainability within society. A key element is the role of technology and its interaction with industry and individuals. The department is divided into four divisions: Technology & Business Studies, Management Science, Climate & Energy Policy and Transportation Science. The department offers a wide range of courses and programs at bachelor, master and PhD level across DTU’s study pro-grams. The department has around 200 employees, with around half coming from abroad.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

Adresse:

Produktionstorvet
2800 Kgs. Lyngby