PhD position on Smart Manufacturing in Green Transportation

PhD position on Smart Manufacturing in Green Transportation

Published Deadline Location
9 May 8 Jun Eindhoven

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Job description

Are you eager to work on smart and sustainable manufacturing in the green transportation sector? And do you have interests in digital twins and AI techniques? Then we are looking for you to support our 'Green Transportation Delta' project as a PhD candidate with a background in operations research, mathematics, industrial engineering, mechanical engineering or computer science. Candidates interested in working on optimization in combination with AI techniques are highly encouraged to apply.  

Project Description

Sustainable transport to achieve the climate objectives both nationally and internationally is getting more and more important. With innovative battery technology as a core component of these developments, the project 'Green Transportation Delta' (GTD) stimulates an integrated approach to research & development (R&D) in the Dutch battery value chain.

The main goal of the project is to accelerate the transition to climate-neutral mobility, which promotes a circular economy and develops a strong, competitive manufacturing industry that contributes to the future earning capacity of the Netherlands. This will be achieved through activities in the development, production, and application of batteries and charging solutions in-house and R&D in the field of battery-electric transport, with an in-depth and multi-year cross-sectoral cooperation at the chain level. The activities within the GTD project are divided into tasks across the battery value chain and target multiple applications in the mobility sector (e.g., passenger cars, buses, trucks, trailers, boats, etc.). These tasks include product innovation through an improved battery management system and modular megawatt chargers, process innovation for production of battery modules and packages, system innovation by connecting charging needs with charging facilities in a smart energy system, and the circular design of the entire battery life cycle from design to recycling. The technological developments in this project facilitate the need and ambition of the Dutch mobility sector toward sustainable transport and less dependence on international suppliers.

TU/e is partner in a work package (WP2) related to process innovation. It aims to develop a smart, flexible, scalable, and sustainable production process of battery modules and packages for various applications in the mobility sector. The work package focuses on the following innovation areas: (i) sustainable factory for efficient use of energy and materials (minimizing waste flows), (ii) digital factory with applications of digital twin, AI, and IT technologies, (iii) flexible manufacturing for high-mix, low-volume, high complexity industry, and (iv) high, smart quality control with data-driven process technology. One of the main challenges here is how to build such an efficient production process in a mixed working environment of human operators, automated machines, and robots.

As a successful applicant, you will perform  research in WP2 of the GTD project described above. While doing research, you will collaborate with other PhD students at Maastricht University and industrial partners in this work package. The research will be concluded with a PhD thesis. A modest teaching load will be part of the job.  

Academic and Research Environment

You will team up with researchers in the Operations Planning, Accounting & Control group (OPAC). OPAC currently consists of 25 staff members, 10 postdocs and 45 PhD students. The group teaches and conducts research in the areas of operations management, transportation, manufacturing operations, reliability and maintenance, and accounting and finance, both at undergraduate and graduate level. The OPAC group has close collaborations with the industry, which gives direct access to challenging operations management problems, new technologies, and empirical data.

Specifications

Eindhoven University of Technology (TU/e)

Requirements

  • A Master's degree in Operations Research, Industrial Engineering, Operations Management, Applied Mathematics, Computer Science, or a related field.
  • Knowledge and experience with simulation, digital twin and machine learning techniques are highly appreciated.
  • Strong analytical and mathematical skills and demonstrated competence for quantitative modelling.
  • Workable knowledge of a programming language like Python and/or Java.
  • Affinity with the areas of smart manufacturing and digital factory.
  • A research oriented attitude.
  • Ability to work in a team and collaborate with the industrial partners in the project.
  • Excellent verbal and written communication skills in English.

Conditions of employment

  • A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
  • A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
  • To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
  • To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
  • A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
  • Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
  • Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
  • A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
  • Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.

Specifications

  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V39.5640

Employer

Eindhoven University of Technology (TU/e)

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Location

De Rondom 70, 5612 AP, Eindhoven

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