Doctoral Researcher in AI for Science
Develop advanced AI foundation models and graph networks for real-time environmental contaminant identification.
Best for:Best for computer science master's graduates with a strong foundation in machine learning, deep learning frameworks, and graph neural networks.
Overview
The University of Luxembourg invites applications for a fully funded doctoral researcher position within the Department of Computer Science and the AI4TECS project. The successful candidate will focus on creating foundation models for contaminant identification using LC-HRMS data, designing hierarchical graph-based models for toxicity prediction, and advancing causal inference methods for transformation modeling. The role involves close collaboration with interdisciplinary teams across environmental chemistry and water-treatment engineering. The position offers a 36-month fixed-term contract with access to high-performance computing resources.
What you'll do
- Develop foundation models capable of identifying emerging contaminants directly from complex LC-HRMS data
- Design hierarchical graph-based models to predict toxicity under uncertainty by linking molecular and system levels
- Advance causal inference methods to predict transformation products under varying treatment conditions
- Write a doctoral dissertation in computer science
- Publish research findings in leading international conferences and high-impact journals
- Present research results at scientific meetings, workshops, and project events
- Participate in optional teaching activities as needed
Requirements
Degree required: Master's degree in computer science or a closely related field
Degree offered: PhD
Language: English; excellent command required
Instruction: English
- Solid background in artificial intelligence and machine learning
- Experience with foundation models such as representation learning and large-scale pretraining
- Experience with graph machine learning including GNNs and hierarchical or probabilistic graph models
- Strong analytical and problem-solving abilities
- Excellent programming skills and familiarity with modern deep learning frameworks
- Applicants must demonstrate at least B2-level proficiency in the language of their thesis
Funding & terms
How to apply
Deadline: N/A · open until filled
Applications must be submitted formally online through the HR system. Early application is highly encouraged as submissions are processed upon receipt. Applications sent via email will not be considered.
- Curriculum Vitae
- Cover letter
- Transcript of all modules and results from university-level courses
- Names, contact information and current position of 3 referees
Contact
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