Descripción de la oferta
Offer Description
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Responsibilities
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.
Requirements
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.
Additional Information
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.
How to Apply
Email: people@cnag.eu
Deadline: 31 July 2026.
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