Predoctoral Research Assistant for the Digital Genomics Group

CNIO - Spanish National Cancer Research Centre; Madrid; On-site; EUR 19,000 - 26,000; Full time

Benefits offered by this job

Health insurance

Meals

Transportation

Childcare

Job summary

CNIO - Spanish National Cancer Research Centre in Madrid seeks a motivated graduate researcher for the EXPOGEN-AI project within the Digital Genomics Group, Cancer Genomics Program. You will integrate exposome, clinical, and genomic data with AI methods to understand lung cancer mutational landscapes.

The role involves collaboration with national and international partners, dissemination of findings through conferences and publications, and contributions to a collaborative and inclusive lab

Qualifications

• MS in epidemiology, data science, bioinformatics, computational biology, biomedicine, or related fields.
• Experience with epidemiological, clinical, genomic, or complex biomedical datasets.
• Knowledge of statistical analysis and data visualization.
• Proficiency in at least one programming language (R and/or Python) and Bash scripting.
• Solid level of spoken and written English for weekly meetings.

Responsibilities

• Integrate and analyze environmental, epidemiological, clinical, and genomic data from cancer cohorts.
• Develop computational and advanced statistical approaches 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 multimodal data integration.
• Collaborate with national and international research partners.
• Disseminate research through lab meetings, conferences, and peer-reviewed publications.
• Contribute to a collaborative, supportive, and inclusive work environment.

Skills

R

Python

Bash scripting

Statistics

Data visualization

English language

Education

MS in epidemiology, data science, bioinformatics, computational biology, biomedicine, or related fields

Tools

HPC clusters

Cloud computing

Job description

We are seeking a highly motivated graduate researcher to join the EXPOGEN-AI project within the Digital Genomics Group, Cancer Genomics Program at CNIO. This is a unique opportunity to investigate how environmental exposures shape the genomic architecture of lung cancer by integrating exposome data, cancer genomics, and advanced artificial intelligence methods.

EXPOGEN-AI is supported by the Community of Madrid (César Nombela grant) and involves national and international collaborations. The project aims to identify mutational signatures, model exposure-driven cancer risk, and develop digital twin strategies to better understand disease mechanisms and support prevention and precision oncology. The project is led by Dr. Karen Gonçalves and will be developed within the Digital Genomics Group, led by Dr. Marcos Díaz-Gay. The group has recently demonstrated significant impact in applying these methodologies across different cancer types, including lung cancer (Díaz-Gay, Zhang, et al. 2025, Nature) and colorectal cancer (Díaz-Gay, dos Santos, et al. 2025, Nature).

Key Responsibilities Of The Position

• Integrate and analyze environmental, epidemiological, clinical, and genomic data from cancer cohorts.
• Develop and apply computational and advanced statistical approaches 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 multimodal data integration.
• Collaborate with national and international research partners.
• Disseminate research through lab meetings, conferences, and peer-reviewed publications.
• Contribute to a collaborative, supportive, and inclusive work environment.

Selection Criteria

• Essential experience and skills:
• M.S. in epidemiology, data science, bioinformatics, computational biology, biomedicine, computer science, or related disciplines.
• Experience working with epidemiological, clinical, genomic, or other complex biomedical datasets.
• Knowledge of statistical analysis and data visualization.
• Proficiency in at least one programming language (preferably R and/or Python) and bash scripting.
• Solid level of spoken and written English (weekly meetings with English-speaking collaborators are expected).
• Desirable experience and skills:
• Experience in cancer genomics, epigenomics, transcriptomics, or other omics data.
• Knowledge of environmental or molecular epidemiology.
• Experience with machine learning or multimodal data integration.
• Experience with high-performance computing (HPC) cluster systems or cloud computing.
• Background or strong interest in lung cancer, exposome research, and somatic mutagenesis.
• Experience with molecular biology techniques (wet lab).

The CNIO Offers

• Incorporation into a Cancer Research Centre of excellence of international relevance.
• Gross annual salary between €19,475 and €25,615.
• Social benefits. Flexible compensation (Health insurance, meals, transportation, childcare).
• Contract linked to a project.