DDSA-DDEA Cross-Academy PhD Scholarships

Danish Data Science Academy (DDSA) and Danish Diabetes and Endocrine Academy (DDEA) invite applications for up to five 2/3 co-funded PhD scholarships of DKK 1,100,000 to visionary young researchers who want to bridge the Danish data science environment with the Danish diabetes and classical endocrinology research environment.  

Applications can be in any field overarching data science and diabetes and/or classical endocrinology research.

Co-supervision is a requirement. You must have an agreement with a principal supervisor within data science employed at a Danish university, as well as a co-supervisor within diabetes or classical endocrinology research affiliated with a Danish research institution.

For questions related to the data science requirements to the project and/or the affiliation of the principal supervisor, you may contact the DDSA Secretariat.

For questions related to the diabetes or classical endocrinology requirements to the project and/or affiliation of co-supervisor, you may contact the DDEA Secretariat.

Deadline for application is Wednesday 7th February 2024 at 12:00

The PhD scholarship must be activated within six months after receiving the grant notification letter (or by further agreement with the DDSA/DDEA).

Expected date of reply is June 2024.

DDSA-DCA Cross-Academy PhD Scholarships

Please note that DDSA and Danish Cardiovascular Academy (DCA) also invite for applications for up to five 2/3 co-funded PhD scholarships of DKK 1,100,000 with the aim to bridge the Danish data science environment with the Danish cardiovascular research environment. You can apply for these here. Please note that you cannot apply for both the DDSA-DDEA Cross-Academy PhD scholarships and the DDSA-DCA Cross-Academy scholarships.

Objective

The DDSA-DDEA Cross-Academy PhD Scholarships aim to bridge the Danish data science environment with the Danish diabetes and classical endocrinology research environment. Applications must be cross-disciplinary between fields of data science and diabetes and/or classical endocrinology.

Data science in this context is a multidisciplinary approach that combines elements from mathematics, statistics, artificial intelligence and computer science to analyze and extract meaningful scientific insights from large amounts of data. Data science thus goes beyond classical and established statistical methods.  Scientific data is typically stemming from a specific scientific domain, and advanced analysis of these data can provide new scientific insights into said domain and therefore data science as a discipline is synergistic to most scientific disciplines.

Application can be within any area of diabetes, metabolism or classical endocrinology research.

The research approach for diabetes, metabolism and classical endocrinology must concern improvement of the understanding of disease mechanisms and improvement of disease prevention, diagnostics, treatment, or rehabilitation within diabetes or classical endocrine diseases.

With the DDSA-DDEA Cross-Academy PhD scholarships, we further aim to:

  • Promote interdisciplinary and cross-sectoral research
  • Create viable networks and collaborations across disciplines and sectors
  • Position Denmark at an international level within data science in diabetes, metabolism or classical endocrinology research
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