PhD Candidate in Data Science for Biomedical Imaging
Develop innovative computational strategies to extract biological insights from complex biomedical imaging data.
Best for:Best for data scientists or computational researchers with a strong background in machine learning and a passion for biomedical applications.
Overview
The Institute for Biological and Medical Imaging (IBMI) at Helmholtz Munich is seeking a motivated PhD candidate to work at the intersection of data science, imaging technology, and biomedical research. The successful applicant will develop robust analysis strategies for diverse datasets, ranging from preclinical experiments to human clinical studies. The role emphasizes scientific curiosity and a deep understanding of data, requiring the candidate to investigate the foundations of imaging pipelines and extract reliable biological information from noisy or heterogeneous sources. You will collaborate with an interdisciplinary team of biologists, clinicians, and engineers to translate advanced imaging technologies into meaningful medical insights.
What you'll do
- Analyze unique preclinical and clinical imaging datasets to uncover novel biological and medical insights.
- Develop and implement innovative data analysis, image processing, and machine learning methods tailored to specific scientific questions.
- Investigate the information content of imaging data and develop strategies for robust inference and validation.
- Implement approaches for uncertainty quantification to ensure the reliability of biomedical conclusions.
- Collaborate with biologists, clinicians, and imaging experts to interpret findings within their biological context.
- Contribute to the development of advanced imaging and sensing technologies for clinical applications.
Requirements
Degree required: Master's degree in Data Science, Computational Biology, Bioinformatics, Mathematics, Physics, Engineering, Computer Science, or a related discipline.
Degree offered: PhD
Language: Excellent communication skills and fluency in English.
Instruction: English
- Strong background in data analysis, statistics, machine learning, or scientific computing.
- Proficiency in programming, preferably in Python.
- Experience working with scientific data.
- Strong analytical and problem-solving capabilities.
- Ability to work independently and collaboratively in an international environment.
- Must hold a Master's degree or equivalent in a relevant field.
- Candidates with foreign degrees must provide a Statement of Comparability for Foreign Higher Education Qualifications.
Funding & terms
How to apply
Applications must be submitted exclusively through the official online application tool. Ensure all required documents are prepared and uploaded as specified in the portal instructions.
- CV
- Letter of motivation
- Academic transcripts of records
Contact
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