Full- or Part-Time | Limited Contract (24 Months) | Starting June 1, 2025
Are you driven to leverage Large Language Models (LLMs) and multimodal data analysis, to create personalized medicine solutions? Join our ambitious GO-TWIN project to develop an innovative AI-powered Digital Twin model for women with ovarian cancer. You will play a crucial role in integrating diverse hospital data to provide personalized treatment strategies and improve patient outcomes.
Your tasks:
- Design and build robust, HL7 FHIR-compatible pipelines for the automated extraction, integration, and harmonization of multimodal data from various hospital sources (clinical records, DICOM images, genomic data, pathology reports).
- Implement privacy-preserving LLMs (e.g., Llama-3-based models) for sophisticated information extraction from unstructured clinical texts and scientific literature to enrich the digital twin. This includes prompt engineering and potentially guided generation techniques.
- Contribute to the architecture and development of the "digital twin" platform, enabling the dynamic representation and analysis of individual patient trajectories.
- Explore and implement XAI methods to ensure transparency and interpretability of AI-driven recommendations for clinical decision support.
- Work closely with clinicians and data scientists to ensure the developed tools meet clinical needs and are validated in real-world settings. Publish your findings in leading journals and conferences.
Your profile:
- An excellent Master's degree (for PhD position) or PhD (for Postdoc position) in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Proven, advanced programming skills, particularly in Python, and experience with deep learning frameworks (PyTorch highly preferred).
- Demonstrable experience in developing and training deep learning models, ideally with a focus on large language models.
- A passion for tackling complex scientific challenges, a creative mindset for developing novel solutions, and a meticulous approach to research and validation.
- A strong analytical and problem-solving mindset, with a keen interest in applying AI to solve complex challenges in personalized medicine.
- You are passionate about open science and open source.
What we offer:
- The opportunity to work on cutting-edge research projects with high societal impact.
- Access to unique, large-scale medical datasets and high-performance computing infrastructure (including NVIDIA A100/H100 GPUs).
- An interdisciplinary and international working environment with close collaboration between AI experts and leading clinicians.
- Funding for conference travel and publications.
- EGYM well pass, corporate benefits and discounts (e.g. Käfer), cafeteria, sports and cultural offers, company bike
- Free use of the library through a branch of the Munich City Library located in the building
- Working in the heart of Munich at Max-Weber-Platz with very good accessibility by public transport such as the subway, S-Bahn or tram
- Company pension plan through the Federal and State Pension Institute (VBL)
- Personal fulfillment through a varied and professionally demanding role with interdisciplinary collaboration.
We look forward to your application!
Contact: PD Dr. Lisa Adams | 089 / 4140 –1084 | Institut für diagnostische und interventionelle Radiologie
Please submit your complete application documents by e-mail including:
-
reference number 25_05_043.
Institut für diagnostische und interventionelle Radiologie
TUM Klinikum
Rechts der Isar
Ismaninger Straße 22
81675 München
E-Mail: keno.bressem@tum.de
If the candidates’ suitability for the position in question is equal, severely disabled applicants shall be given preference. Interview-related costs can, unfortunately, not be reimbursed.