PhD in Agricultural Sciences at Wageningen University & Research (Netherlands) - PhD Scholarships in Agriculture
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PhD in Agricultural Sciences at Wageningen University & Research (Netherlands)

Position overview

Wageningen University & Research, Droevendaalsesteeg, Wageningen, Netherlands, Netherlands
Open

Partial

This open PhD listing is hosted by Wageningen University & Research, based in Netherlands. The advertised research focus covers Agricultural Sciences, Data Science. The application deadline shown for this call is 2026-08-16. Funding notes on this listing: Partial. Key details, funding information, how to apply and a fuller description of the position are collected below from the source vacancy — verify dates and eligibility on the official apply page before submitting an application.

Key details

  • Host institution: Wageningen University & Research
  • Location: Wageningen University & Research, Droevendaalsesteeg, Wageningen, Netherlands
  • Application deadline: August 17, 2026

Funding

Not funded by a EU programme

Funding level (from listing): partial or not via EU framework — confirm on the official call.

How to apply

About the position

Wageningen University & Research invites applications for a PhD position at the intersection of climate change, food systems, and advanced optimization. The successful candidate will develop cutting-edge operations research models to redesign agricultural supply chains that remain resilient under increasing climate uncertainty. The project is hosted by the chair of Operations Research and Logistics and focuses on quantifying how extreme events—such as droughts, floods, heatwaves—affect critical supply chain decisions, including facility location, storage capacity, procurement, and inventory management. The research combines stochastic and robust optimization, uncertainty modelling, large-scale supply chain design, and advanced algorithms, using real-world case studies from vulnerable regions.

Research Context

This PhD is embedded within the Horizon Europe project TIPPING, a large-scale initiative bringing together 16 partners across 10 EU countries. TIPPING develops next-generation climate intelligence tools for agriculture by integrating AI-driven climate modelling, agroecological transition analysis, socio-economic assessment, and decision-support systems. The project directly supports the EU Mission on Adaptation to Climate Change, helping farmers, businesses, and policymakers anticipate and respond to shifting agroecological conditions and climate risks across Europe.

Your Duties

  • Develop advanced quantitative models for resilient agri-food supply chains
  • Write scientific articles for peer-reviewed journals
  • Participate in international project meetings and workshops
  • Contribute to project activities and deliverables within the TIPPING consortium

Candidate Profile

We are looking for a motivated individual with a strong interest in operations research, optimization, and data science. The ideal candidate is eager to work on climate adaptation and resilience in sustainable food systems, using mathematical modelling and data-driven decision-making to create tangible societal impact. A background in operations research, mathematics, industrial engineering, or a related field is required. The position offers the opportunity to collaborate with an interdisciplinary team of researchers and stakeholders across Europe.

Supervision and Work Environment

You will be part of the Operations Research and Logistics chair led by Prof. Sander De Leeuw, and co-supervised by Dr. Peter Kirst, Dr. Meike Reusken, and Dr. Argyris Kanellopoulos. The research group provides a vibrant international environment with expertise in supply chain design, optimisation, and sustainability.

Join us in shaping the next generation of climate-resilient agri-food systems. For application details and further information, please refer to the official announcement by Wageningen University & Research.

Location

Wageningen University & Research, Droevendaalsesteeg, Wageningen, Netherlands

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