AI Researcher in Cancer Biology

hace 4 semanas


Madrid, Madrid, España CNIO A tiempo completo

The Spanish National Cancer Research Centre (CNIO) is seeking an experienced AI researcher to join its team. This role focuses on developing and implementing advanced AI methods to address complex challenges in cancer research.

Job Description

This position offers a unique opportunity to work in a dynamic, multidisciplinary environment, bridging computational and experimental sciences to contribute to impactful discoveries in oncology.

The ideal candidate will have a strong background in AI, machine learning, and data-intensive applications. They will be responsible for:

  • Developing cutting-edge AI methodologies tailored to cancer research needs;
  • Providing computational support and training to CNIO researchers;
  • Collaborating with multidisciplinary teams to integrate AI techniques into experimental workflows;
  • Advancing the development of approaches in data mining and high-performance computing for cancer research;
  • Contributing to grant writing and securing funding for HPC-related projects.

In return, the successful candidate can expect:

Benefits
  • A competitive salary, estimated at around €65,000 per year, considering the company's location and industry standards;
  • A collaborative and supportive work environment at a world-class cancer research center;
  • Interdisciplinary collaboration with leading experimental and computational oncology researchers;
  • The opportunity to contribute to innovative cancer research;
  • A contract linked to a project.
Required Skills and Qualifications

To succeed in this role, candidates should possess:

  • A PhD in Computer Science, Applied Mathematics, Physics, or a related field;
  • A minimum of 4 years of postdoctoral experience in computational research, with demonstrated expertise in AI, machine learning, and data-intensive applications;
  • A proven track record of research excellence with publications in leading journals;
  • Demonstrable experience in HPC architectures, parallel file systems, programming, distributed computing, and data-intensive applications;
  • Experience in one or more areas: image analysis, bioinformatics, information fusion, statistical modeling, predictive analytics, or high-throughput data integration and optimization.


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