Postdoc (1 fte)

Postdoc (1 fte)

Published Deadline Location
19 Sep 31 Oct Eindhoven

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1 Postdoctoral researcher on Data Analytics for Trade Lane Risk Assessments and Control (1.0 fte) within the Operations, Planning, Accounting and Control (OPAC) Group of the School of Industrial Engineering.

Job description

The School of Industrial Engineering is one of the longest-established IE Schools in Europe, with a strong presence in the international research and education community, especially in the field of Operations Management and Operations Research. OM and OR are part of the core of the undergraduate IE program. The graduate programs (MSc and PhD) in Operations Management & Logistics attract top-level students from all over the world. Researchers in the school are member of the Beta research school and participate in industrial activities with members of the European Supply Chain Forum and consortia of research projects.

The group Operations, Planning, Accounting and Control (OPAC) conducts research in the area of Operations Management, with specific emphasis on
  • Planning and Control in Manufacturing, Services, and Supply Chains;
  • Distribution Logistics;
  • Maintenance and Reliability;
  • Finance and Accounting, oriented towards operational processes.

  • Research is generally quantitative in nature, while many of the researchers also engage in empirical research. All research is embedded in Beta, the KNAW-recognized research school for Operations Management & Logistics.

    Postdoc project
    The project 'Data Analytics for Trade Lane Risk Assessments and Control' will conduct research into innovative solutions to optimize trade lane risk management for global pharmaceutical logistics. Together with our industrial partners, we aim to develop advanced data analytics solutions that can significantly improve current risk assessments and result in further trade lane optimization.  The project focuses on the following two topics:

    Topic 1: Machine learning for dynamic risk assessments. Today most lane risk assessments are based on theoretical assessments of supplier capabilities, collected from paper questionnaires or on-site audits, which may be combined with a set of sensor measurements from a small number of test shipments.  In this task, we aim to improve this assessment method by using advanced machine learning methods on large historical shipments data sets.

    Topic 2: Simulation-based optimization of trade-lane packaging options. Besides potential risks, another key consideration in setting up a new trade lane for temperature-sensitive products is the selection of appropriate packaging. In this task, we will develop a simulation tool that can simulate the internal product temperature during a specific trade lane.

    Specifications

    Eindhoven University of Technology (TU/e)

    Requirements

    We are looking for a junior researcher who should have completed (or be close to completion of) a PhD degree in Computer Science, Operations Management, Econometrics, or Industrial Engineering, with a solid background in quantitative research methods. An ideal candidate should have a good basis in machine learning, optimization and is interested in logistics.

    The candidate will work at the School of Industrial Engineering, TU Eindhoven. The research project involves Information Systems (IS) and OPAC groups. We offer a researcher appointment for a period of 12 months with a starting date as early as possible.

    Conditions of employment

    We offer
  • a challenging job in a dynamic and ambitious university;
  • an appointment as a postdoctoral researcher for a period of 1 year with intended starting date as early as possible; the gross salary is in the range of €3.111,- - €4.084,- per month (on a full-time basis); in addition, 8% holiday allowance and 8.3% end of year allowance;
  • a broad package of fringe benefits (including an excellent technical infrastructure, moving expenses, savings schemes, coverage of costs of publishing the dissertation/scientific papers and excellent sports facilities).
  • Specifications

    • Postdoc
    • Engineering
    • max. 38 hours per week
    • Doctorate
    • V39.3042

    Employer

    Eindhoven University of Technology (TU/e)

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    Location

    Den Dolech 2, 5612 AZ, Eindhoven

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