Predoctoral Research Assistant for the Digital Genomics Group (AIPREDG)

Job Description

CNIO - Spanish National Cancer Research Centre is offering a Predoctoral Research Assistant position within the Digital Genomics Group, based in Madrid, Spain. This funded predoctoral contract under the AIPREDG project focuses on the integration of exposome data, cancer genomics, and AI to advance understanding of lung cancer risk.

The successful candidate will work at the intersection of computational biology, environmental epidemiology, and digital health. This role is ideal for a motivated graduate with a strong background in biomedical data science, statistics, and programming who wishes to pursue a PhD in a world-class cancer research environment.

About CNIO: CNIO (Centro Nacional de Investigaciones Oncologicas) is Spain's leading cancer research institute and one of Europe's most recognised oncology centres. The institute employs around 900 scientists and technical staff and is consistently ranked among the top cancer research centres globally.

Key Responsibilities

• Conduct computational analysis of multi-omics datasets (genomics, transcriptomics, epigenomics) in the context of lung cancer
• Integrate exposome data with cancer genomic data to identify environmental risk factors and biomarkers
• Develop and apply machine learning and AI-based models for cancer risk prediction and data integration
• Perform statistical analysis and bioinformatics pipelines on large-scale biomedical datasets
• Contribute to the design and execution of the AIPREDG research project
• Collaborate with interdisciplinary teams including clinical researchers, epidemiologists, and bioinformaticians
• Present research findings at group meetings, national and international conferences
• Contribute to the preparation of scientific publications and reports
• Assist in supervision and training of junior lab members as appropriate

Qualifications

• Required Qualifications:
• Master's degree (or equivalent) in Bioinformatics, Computational Biology, Biomedical Data Science, Epidemiology, Statistics, or a closely related field
• Minimum average grade of 8.5/10 (or equivalent) in undergraduate and postgraduate studies
• Proven experience in biomedical data analysis
• Proficiency in statistical analysis methods
• Programming skills in R and/or Python
• Strong written and verbal communication skills in English
• Preferred Qualifications:
• Experience with multi-omics data (genomics, transcriptomics, epigenomics)
• Familiarity with exposome data analysis and environmental health research
• Knowledge of machine learning and/or deep learning methods
• Experience with lung cancer genomics data
• Background in environmental or molecular epidemiology
• Ability to work independently and as part of an international multidisciplinary team

Experience

- Master's degree or equivalent in a relevant field (Bioinformatics, Computational Biology, Biomedical Data Science, Epidemiology, or Statistics)
- Minimum academic average of 8.5/10 (or equivalent in international grading systems)
- Demonstrable experience in biomedical or omics data analysis
- Strong statistical background
- Programming experience in R and/or Python
- Excellent written and verbal English communication skills
- Candidates must be eligible for an FPI predoctoral fellowship under the Spanish Research Agency (AEI) requirements

Skills Required

• Bioinformatics and computational biology
• Statistical analysis and modelling
• R and/or Python programming
• Genomics and multi-omics data analysis
• Machine learning and AI methods (desirable)
• Data integration and visualisation
• Scientific writing and communication
• Exposome and environmental data analysis (desirable)
• Cancer biology knowledge (desirable)

Additional Information

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