Associate researcher in Genomics Diabetes and Endocrinology - Hiring in process/Finished, not possible to apply

The research group

At the research group Genomics Diabetes and Endocrinology, research is conducted within the purview of precision medicine and metabolic complexity of type 2 diabetes. The research group has been at the forefront of the field of precision medicine and genetics of diabetes for several years. The group formerly established by Senior Prof. Leif Groop and is led by Associate Professor Ola Hansson and consists of 20 research and technical staff. The lab is located at the Clinical Research Centre in Malmö. Here you can read more about our exciting research.

Within the research group, we safeguard a good work environment with respect and consideration in our relationships with each other and strive for a workplace that is perceived as developing and stimulating for all employees. We work constantly to create conditions for job satisfaction, development, and participation for all employees. We care about both physical safety and the psychosocial work environment.

We are hereby looking for an associate researcher for a full-time employment of six months. The position starts 2022-02-01 or by agreement.

Tasks

In 2018 the research group published a method to identify five subtypes of diabetes using simple clinical parameters (Ahlqvist et al, 2018, Lancet D&E).

For this project, supervised by associate professor Emma Ahlqvist, we are looking for a skilled bioinformatician to study the genetic risk factors that lead to susceptibility to diabetes and diabetes related traits.  We will use statistical and genetic methods to analyze GWAS-data from large cohorts of individuals with diabetes. Significant findings will be followed up using bioinformatic methods.

The work can also include other departmental duties.

Qualification

Requirements for the position are:

• PhD in bioinformatics, statistics or an equivalent discipline.
• Good knowledge and experience in statistics, genetics and data analysis in the R software.
• Good knowledge in biology.
• Experience working with large datasets.
  
  

Personal characteristics:

Great emphasis will be placed at personal suitability. The applicant must be motivated, focused and meticulous. The applicant will need to be able to work both independently and as part of a team. The applicant must be able to work in a structured way, be flexible and able to handle multiple projects simultaneously.

Merits for the position are:

• Good knowledge in diabetes research, kidney disease and precision medicine.
• Experience in GWAS analysis and other genomics methods.