As a Postdoctoral Researcher in AI-Enabled Decision Support in Wageningen, you will develop methods and architectures that integrate heterogeneous data and predictive models into adaptive decision-support systems for sustainable crop protection.
You will contribute to the Horizon Europe project STRONG-BIO (Strategic Tool for PhytoPathogen Resistance Oversight in Next-Generation BIOcontrol). Within the Information Technology Group, you will focus on the computational and systems aspects of the project: integrating heterogeneous data and models, developing AI-enabled predictive services, and contributing to an interoperable decision-support system. The three-year postdoctoral trajectory is intended to start around 1 March 2027, shortly after the project launch, so that the first project months can be used for consortium alignment, requirements, data and model inventories, and interface agreements.
Your research will follow a coherent line from architecture and integration foundations, through AI and hybrid model integration, to system validation and generalisation. The aim is not only to implement project functionality, but also to develop reusable scientific methods and architectural principles for trustworthy, adaptive decision-support systems.
You will work closely with STRONG-BIO partners that provide resistance monitoring, eDNA, climate, sensing, epidemiological, evolutionary, and field-validation data and models. You will help turn these heterogeneous inputs into a traceable flow from data and evidence to prediction, recommendation, action, and feedback.
Your duties and responsibilities include:

Design the reference architecture and interoperability approach for integrating heterogeneous biological, environmental, molecular, sensor, and operational data and models.

Develop AI and data-analytics methods, including hybrid approaches that combine data-driven models with epidemiological and evolutionary models.

Develop and integrate an adaptive intelligent decision-support system, addressing uncertainty, provenance, explainability, traceability, and reliability.

Design, implement, and evaluate research prototypes with consortium partners using Living Lab and Core Innovation Farm scenarios.

Publish scientific results, contribute to project deliverables and workshops, and supervise MSc thesis projects related to the research.
Your team
You will work in the Information Technology Group (INF), an international team conducting research and education in artificial intelligence, data science, software engineering, and systems engineering. You will collaborate with INF researchers and MSc students, WUR domain experts, and the international STRONG-BIO consortium.
You will work here
The Information Technology Group develops intelligent, data-intensive, and software-intensive systems for complex challenges in agriculture, food, health, and the environment. In STRONG-BIO, INF contributes expertise in AI, data integration, software and systems architecture, and intelligent decision support. The project provides a strong interdisciplinary environment for developing generalisable methods while validating them in a real European crop-protection setting.
Requirements
You are an independent and collaborative researcher who can translate complex interdisciplinary requirements into rigorous computational methods, architectures, and research prototypes. You are comfortable working across AI, data, software architecture, and life-science application domains.
You also possess:

A PhD in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Systems Engineering, Information Systems, or a closely related field.

A strong research background in one or more of the following: AI or machine learning, data/model integration, data engineering, decision-support systems, software architecture, or knowledge representation.

Experience in designing and implementing research prototypes, with good programming skills, preferably in Python and relevant AI/data-science technologies.

A scientific publication record appropriate to your career stage and the ability to conduct independent research while contributing effectively to an international consortium.

Strong communication and collaboration skills; experience with trustworthy AI, hybrid modelling, knowledge graphs, digital twins, FAIR data, interoperability, or agricultural/life-science applications is an advantage.
In our international working environment there is an increasing amount of communication in English. For this position it is about language level C1.
Contract terms
Wageningen University & Research offers excellent terms of employment . A few highlights from our Collective Labour Agreement include:

sabbatical leave, study leave, and partially paid parental leave;

working hours that can be discussed and arranged so that they allow for the best possible work-life balance;

there is a strong focus on vitality and you can make use of the sports facilities available on campus for a small fee;

a fixed year-end bonus of 8.3%;

excellent pension scheme.
In addition to these first-rate employee benefits, you will of course receive a good salary. Depending on your experience, we offer a competitive gross salary of between € 3.546,- and € 5.538,- for a full-time working week of 38 hours, in accordance with the Collective Labour Agreements for Dutch Universities (CAO-NU) (scale 10). We initially offer a one-year contract, with the intention to extend it by two additional years subject to satisfactory performance, project progress, and the organisation's financial situation.
If you are an internal employee, your current contract is the starting point. Ask your HR Business Partner about your situation specifically. We encourage development and internal mobility within our organisation. Our recruitment and selection policy sets out the conditions that apply specifically to you as a (former) employee. If you have any questions, we are happy to help.
You will work on the greenest and most innovative campus in the Netherlands, in an international and open working environment.

Postdoc AI-Enabled Decision Support and Data Integration

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