of Technical University of Munich (TUM) and Helmholtz Munich’s Explainable Machine Learning Laboratory (EML) We are looking for applications for Fully funded doctoral positions Focused on next generation development Integrated AI systems for scientific discovery. PhD projects offer ambitious researchers the opportunity to contribute to cutting-edge research at the crossroads of the world. Artificial intelligence, explainable machine learning, multimodal foundational models, scientific AI.
Fully considered applications must be submitted by the following deadlines: August 10, 2026, 23:59 CETHowever, review of applications may continue until the position is filled.
Advances in reliable AI for scientific research
Modern artificial intelligence is generating increasingly powerful models, but scientific research requires AI systems that can integrate disparate information sources, external tools, expertise, and human feedback in a transparent and reliable manner.
This PhD project investigates how scientific AI systems can further evolve.
- Reliable.
- Interpretable.
- Adaptable.
- Strong.
- Recognize uncertainty.
This research will focus on understanding how uncertainties, assumptions, errors, limitations, and data provenance propagate across integrated AI systems, and how these systems can be effectively evaluated, updated, and inspected across scientific workflows.
Research field
Selected PhD candidates will contribute to several advanced research topics including:
- Explainable AI (XAI) Mechanistic interpretability of unimodal and multimodal basic models.
- Multimodal alignment and representation learningVision Language Model (VLM), multimodal reasoning, and foundational models.
- Robust adaptation and continuous learningParameter-efficient fine-tuning and model adaptation techniques, etc.
- AI for scienceThis includes applications including agent science workflows, benchmarking, uncertainty estimation, and biological and medical datasets.
The exact direction of the research will be developed jointly by the successful applicant and the supervisory research team.
Collaborative research environment
As a PhD researcher, you will become part of an internationally connected research community that includes:
- of Explainable Machine Learning Laboratory (EML) At Helmholtz Munich.
- of Interpretable and reliable machine learning chair At the Technical University of Munich.
- An international network of collaborating researchers and institutions.
This program provides the opportunity to engage in interdisciplinary research that combines machine learning, computational science, and scientific discovery.
Eligibility requirements
Applicants must have strong academic preparation and technical expertise in artificial intelligence or related fields.
Qualified candidates must have:
- Master’s degree or equivalent qualification in computer science, machine learning, mathematics, statistics, physics, engineering, or a closely related field.
- A strong foundation in machine learning.
- Strong programming skills and experience using modern machine learning frameworks.
- Are you interested in explainable AI, reliable machine learning, multimodal learning, foundational models, AI agents, or scientific AI?
- Excellent communication skills.
- Ability to conduct independent research while contributing effectively within a collaborative team.
Previous papers at major machine learning, computer vision, or natural language processing conferences are considered an advantage but are not required.
The research team particularly welcomes applicants who enjoy combining conceptual research and technical implementation and are interested in helping shape new research directions in trusted scientific AI.
Application requirements
Applicants must submit their application as follows: One unified PDF document Includes:
- Current curriculum vitae (CV).
- Transcripts and degree certificates.
- A short research statement outlining your research interests, relevant experience, and collaboration with the project.
- Contact information 2 academic or professional references.
Please send your application with the following in the subject line: [PhD 2026 EML] To:
[email protected]
Priority application deadline
Candidates are encouraged to submit their applications by the priority deadline.
Important dates:
- Priority deadline: August 10, 2026
- time: 23:59 Central European Time (CET)
Applications submitted by this deadline will be fully considered. Additional applications may be reviewed at a later time until the position is filled.
Opportunity to shape the future of scientific AI
This fully-funded PhD position offers an exciting opportunity for ambitious researchers to contribute to the development of reliable AI systems that can support future scientific discoveries. The successful candidate will work at two of Germany’s leading research institutes, conducting pioneering research that addresses some of the most important challenges in explainable artificial intelligence, multimodal learning, and AI-powered scientific innovation.
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Disclaimer: Global South Opportunities (GSO) is not the organization providing this opportunity. For inquiries, please contact the official organization directly. Please do not submit your application or resume to GSO as it cannot be processed by GSO. Due to the large volume of emails we receive every day, we may not be able to reply to all inquiries. Thank you for your understanding.
