Lunds universitet, Institutionen för kliniska vetenskaper Malmö

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Work duties

The successful applicant will have a strong interest in precision medicine, cardiometabolic diseases (e.g. type 2 diabetes, CVD and obesity) and bioinformatics. Proven ability to program in R, Python, Bash, STATA, and SAS, and experience with machine learning methods (e.g. random forests, neural networks) as is essential and experience with web-based genomic analysis tools and databases (e.g. ANNOVAR, Gene Ontology, API, Variant Effect Predictor app, GTeX, HaploReg, UCSC Genome Browser, DEPICT and MAGENTA). The successful applicant will undertake a PhD project focused on the interplay of genetics, other omics and environmental factors in the development of obesity and associated cardiometabolic disease. The work undertaken will be reported through peer-reviewed publication, which will form the basis of a PhD thesis. The work will focus on the analysis and interpretation of existing data accessible to the GAME Unit, such as the GLACIER Study, VIKING Study, DIRECT Study, RHAPSODY Study, and UK Biobank. The PhD may also involve fieldwork collecting new data in clinical studies. The successful applicant will be expected to work on-site the vast majority of the time, adhere to standard working hours, and take vacation during the standard university vacation periods (late-June to mid-August and Christmas).

Qualifications

Essential characteristics:

  • - A master’s degree (or equivalent) in epidemiology or biostatistics
  • - Experience handling and analyzing complex datasets
  • - Excellent written and oral communications skills (in English)
  • - A background in diabetes, obesity or cardiovascular disease
  • - Experience with statistical methods for analyzing multivariable models
  • - Coding competence in R, Python, Bash, STATA, and SAS, and experience with machine learning methods (e.g. random forests, neural networks) Advanced familiarity with web-based functional genomics tools

 Preferred:

  • - Previous research documented through publication focused on precision medicine


Eligibility
Students with basic eligibility for third-cycle studies are those who- have completed a second-cycle degree- have completed courses of at least 240 credits, of which at least 60 credits are from second-cycle courses, or- have acquired largely equivalent knowledge in some other way, in Sweden or abroad.

The employment of doctoral students is regulated in the Swedish Code of Statues 1998: 80. Only those who are or have been admitted to PhD-studies may be appointed to doctoral studentships. When an appointment to a doctoral studentship is made, the ability of the student to benefit from PhD-studies shall primarily be taken into account. In addition to devoting themselves to their studies, those appointed to doctoral studentships may be required to work with educational tasks, research and administration, in accordance with specific regulations in the ordinance.

Type of employment
Limit of tenure, four years according to HF 5 kap 7§.

Type of employment Temporary position
First day of employment As soon as possible
Salary Monthly salary
Number of positions 1
Full-time equivalent 100
City Malmö
County Skåne län
Country Sweden
Reference number PA2019/2654
Contact
  • Paul Franks, +4640391149
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62
  • SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64
Published 24.Jul.2019
Last application date 13.Aug.2019 11:59 PM CEST

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