The University of Copenhagen is seeking a highly motivated and talented Postdoc fellow to commence on January 1, 2024, in the Merino Group at the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), University of Copenhagen.
The Postdoc fellowship is part of the CBMR International PhD & Postdoc Program.
About us The Novo Nordisk Foundation Center for Basic Metabolic Research’s vision is to strengthen interdisciplinary research that transforms our basic understanding of the mechanisms that underlie cardiometabolic health and disease, and to accelerate this knowledge toward new prevention and treatment strategies. We were established in 2010, and in 2017, we moved into new laboratories and offices in the Maersk Tower.
The Center has around 260 employees who work in an international, highly collaborative research environment across a range of biomedical disciplines. For more information, visit www. cbmr.ku.dk.
Our research The Merino Group is part of a vibrant international research community of computational biologists, statistical geneticists, experimentalists, and clinical translational scientists dedicated to understanding the genetic and environmental complexity of obesity, diabetes, and cardiometabolic diseases. The ability to integrate multidisciplinary skills, techniques, and methods enable us to address key questions at a deeper and more impactful level with the ultimate goal of generating actionable knowledge to inform more effective obesity, diabetes, and cardiovascular prevention and treatment strategies. Our work stands at the forefront of human metabolic diseases, and being member of our group will provide the opportunity to contribute to the large efforts in the field of genomics and human metabolic diseases. To learn more about the Group’s research directions please read more here
The successful candidate should have a Ph.D. in computational biology, computational genomics, biostatistics, computer science, or a related quantitative field and be interested in developing and applying novel computational and statistical methods for analysing single-cell RNA sequence combination with publicly available and individual-level data to gain biological insights into cell-type specific processes that converge into diabetes and cardiovascular disease. The work will contribute to a collaborative international effort to accelerate discovery from genetic maps to biological mechanisms to physiology and clinical translation.
The ideal candidate will have strong programming skills, and a solid background in statistics, and experience with large-scale data analysis, and will be excited to contribute to advancing the science and therapeutic approaches in cardiometabolic diseases. The candidate will develop and apply computational methods integrating single-cell RNA sequencing with GWAS and other functional genomics and metagenomics data to identify key regulatory mechanisms, genes, and cell types that influence diabetes and cardiovascular disease. The postdoctoral fellow will have the opportunity to develop her/his own research projects and interest within this research area and present one’s work at local, national, and international meetings.
Profile The Postdoc fellowship is aimed at early-career researchers with a basic science background or clinicians who aspire to a career in academic medicine. We are particularly interested in candidates who are familiar with integrative research approaches within the broad area of basic cardiometabolic research with an application toward human pathophysiology.
· Ph.D. in computational biology, computational genomics, biostatistics, mathematics, computer science, or a related quantitative discipline.
· Strong background in statistics and computational genomics is required.
· Strong programming skills and in-depth experience with several programming languages is required.
· Experience with Unix/Linux environments, including shell scripting.
· Research experience with large-scale data analysis, such as next- generation sequencing, metagenomics, or other omics data. Algorithm development is highly desirable.
· Motivation to contribute to genomic research of obesity, diabetes, and cardiometabolic diseases is essential.
· Demonstrated critical thinking, rigorous work, and ability to meet deadlines.
· Expected to be a quick learner of new analytical approaches and capable of developing new computational methods for solving complex problems.
· Excellent scientific track record in relation to career stage.
· Strong personal skills and excellent organization and verbal and written communication skills.
· Ability to work effectively independently and collaboratively in a fast- paced academic environment and evolving field.
Eligibility The Postdoc fellowships within the CBMR International PhD & Postdoc Program are open for applicants that hold a PhD degree awarded from a university outside of Denmark. The program is also open for applicants with a Danish PhD degree who can document at least 12 months of full-time research experience from outside Denmark. The PhD degree has to be obtained before January 1, 2024. You are not eligible to apply for the program if you have been employed in a postdoctoral position for more than one year at the University of Copenhagen prior to the commencement of the fellowship.
Terms of employment The employment as Postdoc is a full-time position for 3 years. Starting date is January 1, 2024.
Salary, pension, and terms of employment will be in accordance with the agreement between the Danish Ministry of Finance and AC (Danish Confederation of Professional Associations). Depending on qualifications, a supplement may be negotiated.
Non-Danish and Danish applicants may be eligible for tax reductions if they hold a PhD degree and have not lived in Denmark for the last 10 years.
The position is covered by the Job Structure for Academic Staff at Universities 2020.
Questions For further information about the position, please contact Associate Professor Jordi Merino at firstname.lastname@example.org. Questions regarding the CBMR International PhD & Postdoc Program must be directed to email@example.com. For questions regarding the recruitment procedure, please contact HR at sund-hr- firstname.lastname@example.org.
The University of Copenhagen International Staff Mobility office offers support and assistance to all international researchers on all issues related to moving to and settling in Denmark.
Application Procedure Your online application must be submitted in English via the ‘Apply now’ link below. Furthermore, your application must include the following documents/attachments – all in PDF format:
· Cover letter expressing the motivation and previous research experience of the applicant (max. one page)
· Curriculum vitae
· Copy of the PhD degree certificate and the master’s degree certificate. In case the PhD has not yet been completed, a written statement from the supervisor is acceptable, confirming it will be obtained before January 1, 2024.
· List of publications
· References (name and contact details of at least two references)
Application Deadline: June 18, 2023, at 23.59pm CET.
We reserve the right not to consider material received after the deadline and not to consider applications that do not live up to the abovementioned requirements.
The further process After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed, each applicant can comment on the part of the assessment that relates to the applicant him/herself.
You can read about the recruitment process at www. employment.ku.dk/faculty/recruitment-process.
The applicant will be assessed according to Ministerial Order No. 242 of March 13, 2012, on the Appointment of Academic Staff at Universities.
The University of Copenhagen wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of their personal backgrounds.