Job
- Level
- Experienced
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Munich
- Working Model
- Onsite
Job Summary
In this role, you will process clinical datasets, develop machine learning pipelines, evaluate models, and apply survival and predictive modeling methods to real-world clinical data.
Job Technologies
Your role in the team
- Processing, harmonization, and analysis of heterogeneous clinical and longitudinal datasets.
- Development of reproducible data processing and machine learning pipelines.
- Development and evaluation of machine learning, transformer, and LLM-based methods.
- Application of survival and predictive modeling to clinical outcomes.
- Evaluation of model performance, interpretability, and generalizability across datasets.
- Zusammenarbeit mit klinischen und methodischen Experten.
- Dissemination of results through scientific publications and presentations.
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Our expectations of you
Education
- Master's degree or equivalent in Data Science, Computer Science, Medical Informatics, Bioinformatics, Statistics, Artificial Intelligence, or a related field.
Qualifications
- Strong programming skills in Python and PyTorch.
- Machine learning and deep learning.
- Longitudinal or time-series data.
- Large language models or natural language processing.
- Transformer architectures and representation learning.
- Clinical or biomedical data analysis.
- Survival analysis and statistical modeling.
- Strong analytical and problem-solving skills.
- Ability to work independently and in an interdisciplinary team.
- Excellent written and spoken English.
- Strong motivation, scientific curiosity, and persistence, with the ability to independently tackle complex and challenging problems.
Experience
- Experience in several of the following areas:
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What we offer
- A PhD project at the leading edge of clinical AI and personalized oncology, working on emerging AI methods and their application to large-scale real-world clinical data.
- Access to large-scale clinical datasets and modern computational infrastructure.
- Close collaboration with AI researchers, clinicians, and methodological experts from different disciplines.
- A broad interdisciplinary environment in which you can develop expertise across the full clinical AI spectrum from data engineering and representation learning to LLMs, transformer models, and survival analysis.
- Opportunities to publish in leading scientific venues, present at international conferences, and pursue professional development that supports you in becoming a well-rounded expert in clinical AI and medical data science.
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Benefits
Health, Fitness & Fun
Work-Life-Integration
Topics You Will Work On
Job Locations
About Your Employer
Ludwig-Maximilians-Universität München
The Ludwig-Maximilians-Universität München (LMU) is one of the most prestigious and largest universities in Germany. With its outstanding research and teaching, it is a top destination for students from all over the world.
Description
- Company Size
- 250+ Employees
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Education System
PhD Candidate - Clinical AI and Medical Data Science
- Location
- Munich
- Working Model
- Onsite
- Diversity
- Open for all genders
- English Only
- English only required
