International PhD Fellowships in Biostatistics and Bayesian Inference, Denmark

  •  PhD, Fellowship
  •  05-Mar-2024
  •   Denmark
  • $$  Full-time employment for 3 years

Are you passionate about advancing statistical methodologies to address pressing public health challenges? The Department of Public Health at the University of Copenhagen, Denmark, is delighted to announce a International PhD Fellowships in Biostatistics and Bayesian Inference. This exciting opportunity aims to foster innovative research in the field of biostatistics, particularly in understanding the dynamics of mental health outcomes over time through sophisticated statistical approaches.

This scholarship aims to support highly qualified and motivated individuals in pursuing doctoral research in the area of biostatistics, focusing on Bayesian inference and its applications in longitudinal data analysis. The successful candidate will engage in developing and applying statistical methodologies tailored to longitudinally observed cohort data, with a particular emphasis on partially identified and observed continuous processes influencing mental disorders.Why study at University of Copenhagen?Studying at the University of Copenhagen offers a unique opportunity for academic excellence in a historic and vibrant European city. As one of Europe’s premier research institutions, it provides access to cutting-edge facilities, renowned faculty, and a global network of peers.

Københavns Universitet Information

Københavns Universitet Grants

International PhD Fellowships in Biostatistics and Bayesian Inference, Denmark Established in 1479, Københavns Universitet (University of Copenhagen) is a non-profit public higher education institution located in the urban setting of the large city of Copenhagen (population range of 1,000,000-5,000,000 inhabitants), Capital Region of Denmark. Officially accredited and/or recognized by the Uddannelses- og Forskningsministeriet (Ministry of Higher Education and Science, Denmark), Københavns Universitet (KU) is a very large (uniRank enrollment range: 35,000-39,999 students) coeducational higher education institution. Københavns Universitet (KU) offers courses and programs leading to officially recognized higher education degrees in several areas of study. See the uniRank degree levels and areas of study matrix below for further details. This 540 years old higher-education institution has a selective admission policy based on students' past academic record and grades. International applicants are eligible to apply for enrollment.

Eligibility Criteria

  • Eligible Countries: Open to applicants from all countries
  • Acceptable Course or Subjects: The scholarship will be awarded in any subject offered by the University of Copenhagen.
  • Admissible Criteria: Applicants must meet all the following criteria:
    • Hold a candidate degree in mathematics, statistics, or engineering sciences
    • Possess strong skills in theoretical and applied statistics
    • Ability to communicate research findings effectively through teaching, presentations, and publications.

Offered Benefits

The successful candidate will receive a competitive salary, pension, and terms of employment in accordance with the agreement between the Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State. The monthly salary starts at approximately 27,800 DKK (roughly 3,700 EUR), plus pension, depending on seniority.

Join us in advancing biostatistics and contributing to improving public health outcomes through cutting-edge research. Apply now and embark on an enriching academic journey at one of Europe’s top-ranking universities!

Application Process

Interested candidates are required to submit their applications electronically by the deadline of March 5, 2024, 23:59 pm CET. The application package should include:

  1. A motivated letter of application (max. one page)
  2. Curriculum vitae detailing relevant experiences
  3. Certified copies of academic transcripts and diplomas
  4. Publication list (if available)
  5. Documentation of knowledge on advanced computational methods
  6. Reference letters.
Apply Here
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