PhD Position Adaptive Optimization and Learning Methods for Transportation Systems

PhD Position Adaptive Optimization and Learning Methods for Transportation Systems

Published Deadline Location
14 Feb 29 Mar Delft

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Are you passionate about bringing in behavioral phenomena for decision-making in transport and logistics?

Job description

One of the biggest challenges for transportation systems is how to wisely utilize the available resources while responding to the demand.  According to Eurostat, 20% of road freight kilometres in the EU in 2020 were driven by empty vehicles and this is similar for other modes of transportation. There are various reasons for the underutilization of transportation capacity. Firstly, there are uncertainties in the system, e.g., demand is fluctuating, the travel and service times vary significantly. In order to cope with that, operators frequently end up allocating more resources than needed. Secondly, transport systems have complex supply-demand interactions which makes it difficult to optimize the decisions on different resources. Underutilization of capacity entails costs that do not generate revenue and contribute to CO2-emissions, whereas the transportation sector is striving for sustainability goals. Being able to adapt the decisions – e.g., the network design, allocation of capacity, routing and scheduling - according to evolving demand and conditions in the transport network is a promising direction to improve the utilization of available resources.

ADAPT-OR project is funded by European Research Commission for Fundamental Research. The aim of ADAPT-OR is to develop self-learning capabilities towards adaptive transportation systems by leveraging the intersection of operations research, behavioural modelling and machine learning methodologies. The idea is to make use of information from the system itself across different decision-making levels, from the users and from the external environment in a self-learning manner in order to continuously adapt the decisions at different levels. For example, depending on the trends in behavior for a given delivery service, the network design can be adapted.

This particular PhD project focuses on bringing behavioral understanding into the adaptive optimation models within ADAP-OR. This entails that behavioral foundations need to be exploited for optimizing transport decisions. The representation of user behavior might strongly benefit from machine learning methodologies in order to have a self-learning capability also in terms of capturing the trends and evolutions in behavior. Integration of behavioral models brings in challenges for the tractability of the optimization models and model-based learning will be one of the solutions for this. The PhD student will be interacting with the other researchers working for the ADAPT-OR project in order to make use of the synergies as well as for the development of the case studies to showcase the benefits of the methodologies.

The start date of the PhD is flexible within 2024 and ideal start date would be around September. The PhD student will be joining the group of Bilge Atasoy, working on adaptive transportation and logistics. The group has members with expertise on operations research, behavioural modelling and machine learning with applications in transportation. There is a vivid interaction in the group to foster collaboration and transfer of knowledge. The project will have opportunities for collaborations with leading universities worldwide. There is also the opportunity to get teaching experience in topic-wise related courses. 

Specifications

Delft University of Technology (TU Delft)

Requirements

We are looking for a candidate who has operations research background and also preferably interest and knowledge in behavioral models in transportation. As the project is a multi-faceted one, we expect candidates with an appreciation of social challenges in the context of implementing new sustainable frameworks and business models.

  • Master of Science (MSc) diploma in Operations Research, Transportation, Logistics, Industrial Engineering, Applied Mathematics or any other related field.
  • Attitude to function both in a team and independently.
  • Willingness to conduct multidisciplinary research in collaboration with both scientific and industrial partners.
  • Drive for excellence in research.
  • TOEFL or IELTS English proficiency tests for all applicants except those graduated from an MSc program that was taught in English. The minimum requirement of an TOEFL score of 100 IELTS of 7.0 per sub-skill (writing, reading, listening, speaking). 

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Conditions of employment

Fixed-term contract: 1,5 years + 2,5 years (after go decision).

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Employer

Delft University of Technology

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Department

Faculty Mechanical Engineering

From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.

Click here to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.

Specifications

  • PhD
  • Engineering
  • 36—40 hours per week
  • €2770—€3539 per month
  • University graduate
  • TUD05004

Employer

Delft University of Technology (TU Delft)

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Location

Mekelweg 2, 2628 CD, Delft

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