CNAG: HER-CARE PhD position

Offer Description

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Determine how both germline variants and somatic mutations in key breast‑cancer genes affect the structure of the encoded proteins. Build a classifier rooted in AI techniques. This is a purely dry‑lab position with no wet‑lab work required.

• Master’s degree or equivalent in Computer Science, Bioinformatics, or a related field.
• Strong programming skills in R.
• Background in machine learning and/or protein structure.
• Mobility rule: did not reside or carry out main activity in Spain for more than 12 months in the 3 years immediately before the recruitment date.
• Must be a doctoral candidate; not yet hold a PhD degree at the date of recruitment.

• Teaching experience: supervision of at least one bachelor or master student and co‑supervision of a practical course.
• PhD coursework and training: 100 hours of coursework, participation in HER‑CARE network‑wide training events, and at least two graduate school courses.
• At least two conference presentations (poster or oral) and two or more first‑author publications in peer‑reviewed journals; participation in at least one public outreach activity.
• International mobility: 3 months at the Netherlands Cancer Institute (NKI) in the Genetic Epidemiology of Breast Cancer group, and 3 months at Proteotype Diagnostics Ltd in Cambridge, UK.
• Three‑year full‑time predoctoral contract with remuneration in line with MSCA‑DN funding regulations.
• Proposed start date between September 1, 2026 and January 1, 2027.

Email: people

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