• Reference: TECCCG25
• Start date: 18/09/2025 0:00:00
• Expiration Date: 02/10/2025 23:59:00
  
  

The Computational Cancer Genomics lab investigates cancer-type and condition-specific mutation effects by analyzing large-scale cancer genomics. The team is now seeking a highly motivated Technician. The person will maintain and analyze large-scale cancer/human genomics datasets. In addition, our research aims to integrate computational and experimental approaches to understand context-specific, especially mutation-specific, changes in protein–protein interaction (PPI) networks. We focus on how genetic alterations rewire molecular interaction networks and how these changes contribute to cancer phenotypes. Ultimately, our goal is to translate these findings into precision oncology, by linking mutation-driven PPI alterations to patient-specific therapeutic strategies.

Roles And Responsibilities Of Proposed Position

• Collection, curation, and maintenance of publicly available and in-house cancer genomics datasets.
• Development and maintenance of standard computational pipelines for reproducible data analysis.
• Experimental setup and execution of protein–protein interaction assays to investigate mutation-specific network rewiring.
• Integration of computational and experimental data to study the impact of genetic alterations on protein interaction networks.
• Collaboration with team members to connect mutation-driven network changes with precision oncology applications.
  
  

Selection Criteria

• Master’s degree or equivalent. PhD is not mandatory but it would be a plus.
• Experience in Molecular Biology, Genetics, Bioinformatics, Computational biology, Statistics or relevant field.
• Experience in protein–protein interaction (PPI) analysis, either experimentally or computationally.
• Familiarity with large-scale data integration, particularly combining genomics, transcriptomics, and protein interaction datasets.
• Ability to design, optimize, and troubleshoot experimental assays related to PPI studies.
• Experience in big-data analysis frameworks and handling complex biological datasets.
• Background in functional genomics or systems biology approaches will be highly valued.
• Technical skills:
• Proficiency in R or Python for data processing and analysis.
• Familiarity with workflow management systems and/or cluster computing environments.
• Basic experience in NGS data analysis (alignment, mutation calling).
• Hands-on experience with molecular cloning techniques.
• Familiarity with yeast two-hybrid (Y2H) assay design, setup, and screening.
• Experience in DNA/RNA extraction, PCR, and gel electrophoresis.
• Competence in library preparation, plasmid construction, and maintenance of yeast/bacterial strains.
• Understanding of protein–protein interaction assays.
• Strong problem-solving skills and ability to optimize protocols.
• Excellent communication and organizational skills.
• Ability to work collaboratively in a multidisciplinary team.
• High attention to detail, motivation to learn, and adaptability.
• The successful candidate will have the ability to communicate effectively, both speaking and in writing, in English. Applications must include a detailed CV in English.
• Initiative, flexibility and the ability to solve everyday problems related to your duties and with regard to workplace relations.
  
  

The CNIO Offers

• The opportunity to be part of one of the few European Cancer Research Centres of excellence.
• An excellent working, multidisciplinary environment.
• Competitive salary.
• Contract linked to a project.