PhD Position Decentralized and Trustworthy AI Pipelines (EU project WALTZ)

Public administrations hold the data for better public services but cannot pool it. We aim to build decentralized AI pipelines that let them learn from data they can never expose, in the EU project WALTZ.

Job description

The Horizon Europe Innovation Action WALTZ (Workflow-Driven AI-Enabled Lawful and Trusted Data Spaces for Public Authorities) builds a trusted "system-of-systems" data stack that turns heterogeneous administrative data into governed, AI-ready assets, validated in six public-sector pilots. TU Delft leads its task on AI-ready training and evaluation pipelines using real and synthetic data. Public authorities cannot ship their data to a central trainer, the participants in such a pipeline cannot all be assumed honest, and the models they increasingly want to deploy are LLM-based, whose failures are semantic rather than crashes.

We aim to build training and inference pipelines that work across administrative boundaries, and evaluation methods that say something honest about how far they can be trusted. Initial concrete task ideas include:

• design decentralized and federated pipelines that combine real and synthetic data across organisational boundaries without a central aggregator, under controlled mixing strategies that address data scarcity and distribution shift;
• make them resilient to Byzantine participants, and to poisoning of the synthetic data supply;
• quantify what leaks: membership inference and reconstruction against models trained on real-synthetic mixes, and the utility cost of differentially private generation;
• treat LLM-based components as a distributed system: replicate inference across diverse models, study how their failures correlate, and use quorum and semantic-agreement mechanisms to turn individually unreliable answers into trustworthy ones;
• build the evaluation side: benchmarks, cross-validation schemes, reporting protocols — covering accuracy, robustness, bias, generalisation and privacy leakage, released as open, reproducible software.

You will be based at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), in the Distributed Systems group of the Department of Software Technology, supervised by Dr Jérémie Decouchant, whose work spans Byzantine fault tolerance, decentralized learning and trustworthy AI systems. TU Delft's DelftBlue and DAIC GPU clusters are available for large-scale experiments.

WALTZ has more than thirty partners, so your work will not stay in the lab: you will collaborate with research groups across Europe and see your methods stress-tested by real public authorities. Alongside your research you will publish at top venues, follow the TU Delft Graduate School doctoral programme, and take on a modest teaching and supervision load (up to 15%).

Job requirements

• An MSc (completed, or close to completion) in Computer Science, Data Science, Artificial Intelligence, Electrical Engineering or a closely related field.
• A solid foundation in machine learning and/or distributed systems. Familiarity with federated or decentralized learning, fault tolerance, generative models, privacy-preserving ML, or LLM-based systems is a strong asset.
• Strong programming skills in Python and hands-on experience with a modern deep learning framework (e.g. PyTorch), including work on Linux-based GPU/HPC clusters.
• Demonstrable interest in trustworthy AI: privacy, robustness, adversarial behaviour, evaluation methodology and reproducibility.
• Strong analytical skills and the independence to carry a research agenda over four years, combined with the discipline to meet project deliverable deadlines.
• Excellent command of written and spoken English. Non-native speakers without an English-taught degree must meet the TU Delft English language requirements (e.g. TOEFL iBT 90 or IELTS 6.5 overall).
• A collaborative attitude: you enjoy working in a large international consortium and can explain your work to non-academic stakeholders such as public administrations.
• Commitment to open science: publishing code and benchmarks, and contributing to open-source software.

Conditions of employment 
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 €3204 - €4051 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.  

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.  

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.  

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Jérémie Decouchant, via [email protected].

Application procedure
Are you interested in this vacancy? Please apply no later than 24 Sep 2026 via the application button and upload the following documents:

• a cover letter (max. 1 page) explaining your motivation and your fit with the research topic;
• your CV, including a list of publications if applicable;
• transcripts of your BSc and MSc studies;
• a copy of your MSc thesis, if applicable;
• proof of English language proficiency, if applicable.
• Optionally, you may add links to code repositories you are proud of.

You can address your application to Dr. Jérémie Decouchant.

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. 

Please note:

• You can apply online. We will not process applications sent by email and/or post. 
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.
   

#EUfunded This is an EU funded project, named WALTZ, with project number 101342260, within program Horizon Europe