Predoctoral Research Assistant in Digital Genomics and AI
Join a cutting-edge project integrating exposome data, cancer genomics, and AI to uncover environmental influences on lung cancer.
Best for:Best for motivated graduate researchers with a strong background in computational biology, bioinformatics, or related fields, interested in AI-driven cancer genomics research.
Overview
This position offers a unique opportunity to work within the Digital Genomics Group at the Spanish National Cancer Research Center (CNIO) in Madrid. The role focuses on investigating how environmental exposures influence the genomic architecture of lung cancer by combining exposome data, cancer genomics, and advanced artificial intelligence methods. The project, supported by the Community of Madrid, aims to identify mutational signatures, model exposure-driven cancer risk, and develop digital twin strategies for precision oncology. The successful candidate will collaborate with national and international partners, contributing to both research and knowledge dissemination in a collaborative and inclusive environment.
What you'll do
- Integrate and analyze environmental, epidemiological, clinical, and genomic data from cancer cohorts.
- Develop and apply computational and advanced statistical methods for exposome-informed cancer research.
- Analyze somatic alterations and mutational signatures in relation to environmental and lifestyle exposures.
- Apply machine learning and AI approaches to integrate and interpret multimodal genomic and exposome data.
- Collaborate with national and international research partners to advance the project’s objectives.
- Disseminate research findings through lab meetings, conferences, and peer-reviewed publications.
- Contribute to a collaborative, supportive, and inclusive research environment.
Requirements
Degree required: Master's degree or equivalent in Biological Sciences, Bioinformatics, Computational Biology, or a related field
Language: English; proficiency required for research communication and collaboration
Instruction: English
- Proven experience in data integration and analysis, particularly in genomics or related fields
- Familiarity with computational and statistical methods for biological data analysis
- Experience with machine learning and AI techniques applicable to genomics
- Strong analytical and problem-solving skills
- Ability to work collaboratively in a multidisciplinary research environment
- Open to applicants with a Master’s degree or equivalent in relevant fields
- No specific nationality or residency restrictions mentioned
Funding & terms
How to apply
Deadline: 2026-11-01 (Europe/Madrid)
Applicants should submit their CV, a motivation letter, and 2-3 reference contacts via email to empleo@cnio.es. The subject line should clearly indicate the position being applied for.
- CV
- Motivation letter
- 2–3 reference contacts
Contact
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