The Research Institute Children's Cancer Centre at the University Medical Center Hamburg-Eppendorf is looking for a highly motivated research assistant (PhD/Postdoc) in the Computational Pediatric Oncology working group (headed by Prof. Dr. Michael Bockmayr) starting 01.01.2027. A later start can be accomodated in principle. Doctoral studies may be pursued as part of this position.

The research group is dedicated to the development of quantitative methods for paediatric hematology and oncology. You will be involved in an exciting project that uses machine learning methods to enable more accurate predictions of diagnosis, survival, and therapy response in cancer from high-dimensional omics data, particularly DNA methylation data.

Strong individualized support is guaranteed throughout the entire period. In addition, you can expect a motivated and dynamic team of physicians, natural scientists, bioinformaticians, technical assistants, and students at the Research Institute, who are investigating pediatric cancers as part of various projects and with different approaches.

Your tasks:

• Development and evaluation of clinically relevant classification algorithms using machine learning methods on high-dimensional omics datasets
• Close collaboration with partners in the field of machine learning and other research groups at the Children’s Cancer Center
• Presentation of research results at international conferences and publication as first author in recognized journals

The position is temporary for two years due to third-party funding and project duration and may be extended.

• Completed scientific university studies in the field of machine learning, bioinformatics, computer science, data science, applied mathematics, physics, biomedical engineering or another relevant field
• Proven programming experience, especially in Python, good knowledge of ML frameworks such as PyTorch or TensorFlow. Programming experience in R is a plus.
• Excellent knowledge of current machine learning methods
• Excellent communication skills and ability to collaborate across disciplines
• Proficiency in written and spoken English; familiarity with German is a plus
• Experience with representation learning, transformer architectures, foundation models and explainable AI (XAI) is a plus.
• Knowledge of DNA methylation data processing, in particular array- and (Nanopore-) sequencing-based data, is a plus but not mandatory, as we care more about your computational skills.
• Knowledge of UNIX-based operating systems and version control software is desirable

We look forward to receiving a detailed application including a letter of motivation, CV, references, degree certificates, transcript of records and, if possible, links to code examples, theses or publications.

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