Technische Universität Dresden
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PhD in AI-Driven Cancer Prevention Using Digital Health and Nutrition Data Dresden University of Technology in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Four years of funding (3+1, three years with the possibility to extend for one year). The post is described as full promotion and financing is marked yes.
Deadline
Oct 15, 2026
Country
Germany
University
Technische Universität Dresden

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About this position
PhD project at Dresden University of Technology (TU Dresden) in collaboration with the German Cancer Research Center (DKFZ) Dresden.
The project focuses on AI-driven cancer prevention using app-collected digital health data, nutrition data, structured food and nutrition databases, and local cancer incidence data. Research aims include identifying modifiable dietary, behavioral, and metabolic risk patterns and building scalable, interpretable prevention models.
Academic keywords: cancer prevention, digital health, app-collected data, nutrition data, food databases, artificial intelligence, large-scale data analysis, risk prediction, bioinformatics, data science, computer science.
Eligibility: Applicants should hold a master's degree or equivalent in data science, bioinformatics, computer science, or a related field. Strong quantitative skills and experience with R and Python are expected. Experience with cohort data, app-based data, electronic health records, nutrition data, or real-world data is desirable.
Funding: Four years of funding (3+1; three years with the possibility of a one-year extension). The post is marked as fully promoted/financed.
Location: Dresden, Germany. Start date: flexible within 2026 / as soon as possible.
Deadline: 15 October 2026.
How to apply: Submit your application through the HFA application portal and include the required documents: motivation letter, CV, certificates/diplomas, transcripts, research proposal, and references.
Funding details
Four years of funding (3+1, three years with the possibility to extend for one year). The post is described as full promotion and financing is marked yes.
What's required
Master's degree or equivalent qualification in data science, bioinformatics, computer science, or a related field. Strong quantitative skills and experience with R and Python are expected. Experience with cohort data, app-based data, electronic health records, nutrition data, or real-world data is desirable.
How to apply
Apply via the HFA application portal. Prepare the required documents: motivation letter, CV, certificates/diplomas, transcripts, research proposal, and references. For project questions, contact the listed project email; for application-process questions, contact the Hector Fellow Academy Office.
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