PhD Candidate – Clinical AI and Medical Data Science (m/f/x)

LMU; München; Hybrid; EUR 54.000 - 68.000; Vollzeit

Benefits dieser Stelle

PhD in clinical AI

Zusammenfassung

LMU Munich is seeking a PhD Candidate – Clinical AI and Medical Data Science to advance AI methods on large real-world clinical data. You will process and harmonize datasets, develop reproducible pipelines, and apply survival and predictive modeling to outcomes.

Collaborate with AI researchers, clinicians, and methodological experts in a broad interdisciplinary environment and publish in leading venues.

Qualifikationen

• Master's degree or equivalent in a quantitative field.
• Strong programming and data science skills required.
• Experience with clinical or biomedical data analysis is advantageous.

Aufgaben

• Process, harmonize, and analyze heterogeneous clinical datasets.
• Develop reproducible data processing and ML pipelines.
• Evaluate ML, transformer, and LLM-based methods for clinical use.
• Apply survival and predictive modeling to outcomes.
• Collaborate with clinicians and researchers across disciplines.
• Publish results and present at conferences.

Kenntnisse

Python

PyTorch

Machine learning

Survival analysis

Data harmonization

Longitudinal data

LLMs / NLP

Data analysis

Team collaboration

English communication

Ausbildung

Master's degree or equivalent in Data Science, Computer Science, Medical Informatics, Bioinformatics, Statistics, Artificial Intelligence, or a related field

Tools

Python

PyTorch

Jupyter / notebooks

Jobbeschreibung

Ludwig-Maximilians-Universität München is a leading research university in Europe. Since its founding in 1472 it has been committed to the highest international standards of excellence in research and teaching.

Institution Faculty of Medicine - Pathologisches Institut der LMU

Remuneration group TV-L E13

Full-time / Part-time Full-time (100%)

Start date as soon as possible

About us:

The Institute of Pathology at LMU Munich is one of the largest university pathology departments in Germany. As a key partner of the LMU Medical Center, we provide state-of-the-art pathological diagnostics to the Großhadern and Downtown campuses, as well as to numerous external hospitals and private practices. For more information, please visit here .

We are looking for you:

PhD Candidate – Clinical AI and Medical Data Science (m/f/x)

Your tasks and responsibilities:

• 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
• Collaboration with clinical and methodological experts
• Dissemination of results through scientific publications and presentations
• Master's degree or equivalent in Data Science, Computer Science, Medical Informatics, Bioinformatics, Statistics, Artificial Intelligence, or a related field
• Strong programming skills in Python and PyTorch
• Experience in several of the following areas:
  • 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
• 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
• Salary according to TV-L E13 , subject to the applicable institutional regulations

Applicants with severe disabilities and those deemed equivalent within the meaning of Section 2(3) of SGB IX will be given preferential consideration if equally qualified.

Also possible in a part-time capacity.

People with disabilities who are equally as qualified as other applicants will receive preferential treatment.

Benefits:

• 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
• Salary according to TV-L E13 , subject to the applicable institutional regulations

Applicants with severe disabilities and those deemed equivalent within the meaning of Section 2(3) of SGB IX will be given preferential consideration if equally qualified.

Also possible in a part-time capacity.

People with disabilities who are equally as qualified as other applicants will receive preferential treatment.

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