PhD Scholarship in Pattern Recognition and Machine Learning for Kidney Transplant Prediction, Netherlands

  •  PhD
  •  15-Jan-2026
  •   Australia
  • $$  Varies

The University Medical Center Groningen (UMCG) invites applications for a PhD Scholarship in Pattern Recognition and Machine Learning for Kidney Transplant Prediction, funded by the Dutch Kidney Foundation and NWO. This position focuses on developing AI models to predict kidney transplant outcomes using machine learning on biomarkers from clinical data, perfusion fluid, and biopsies, aiming to boost donor kidney utilization and patient survival rates.

This scholarship is available to Aboriginal and/or Torres Strait Islander students who are applying to commence the Juris Doctor at the University of Melbourne. Applicants must apply through Graduate Access Melbourne, demonstrate disadvantaged socio-economic circumstances, and meet all program entry requirements.

The University Medical Center Groningen (UMCG) is one of the largest academic hospitals in the Netherlands, established in 2005 through the merger of the University of Groningen and the Academic Hospital Groningen. Employing over 10,000 staff, it serves as the primary referral center for complex care in the northern Netherlands, specializing in advanced treatments such as organ transplants and focusing research on healthy aging.

The University of Melbourne Information

The University of Melbourne Grants

PhD Scholarship in Pattern Recognition and Machine Learning for Kidney Transplant Prediction, Netherlands Established in 1853, The University of Melbourne is a non-profit public higher education institution located in the urban setting of the large city of Melbourne (population range of 1,000,000-5,000,000 inhabitants), Victoria. Officially accredited and/or recognized by the Department of Education and Training, Australia, The University of Melbourne (UNIMELB) is a very large (uniRank enrollment range: over-45,000 students) coeducational higher education institution. The University of Melbourne (UNIMELB) offers courses and programs leading to officially recognized higher education degrees such as pre-bachelor degrees (i.e. certificates, diplomas, associate or foundation degrees), bachelor degrees, master degrees, doctorate degrees in several areas of study. See the uniRank degree levels and areas of study matrix below for further details. This 166 years old higher-education institution has a selective admission policy based on students' past academic record and grades. The admission rate range is 70-80% making this Australian higher education organization a somewhat selective institution. International applicants are eligible to apply for enrollment.

Eligibility Criteria

  • Eligible Countries: All nationalities.
  • Acceptable Course or Subjects: The scholarship will be awarded in Pattern Recognition, Machine Learning, Artificial Intelligence, Computer Science, or related fields, focused on kidney transplant prediction.
  • Admissible Criteria: To be eligible, applicants must meet all the following criteria:
  • Recently completed a Master’s degree in Artificial Intelligence, Computer Science, Medicine, or a related field.

  • Demonstrable experience with deep learning, medical image analysis, and/or medical imaging.

  • Excellent English communication skills (written and spoken).

  • Independence, initiative, and strong organizational skills.

Offered Benefits

  • 4-year contract with competitive salary and excellent secondary conditions.

  • Multidisciplinary environment in a top research consortium with clinical impact.

  • Supervision by experts in nephrology and AI; collaboration with national/international teams.

  • Opportunities for conference presentations, publications, and personal development.

Application Process

To apply for this scholarship, applicants must submit via the digital application form on the UMCG job page (linked in original posting). Applications close January 15, 2026. Include CV, motivation letter, and references. Confirmation email sent within 30 minutes. Contact Prof. Martin de Borst (+31 6 527 24813) or Prof. George Azzopardi (+31 50 363 6533) for queries.

Apply Here
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