De afdeling Neurochirurgie heeft een vacature voor de functie van (arts-)onderzoeker binnen de neurovasculaire onderzoekslijn. Binnen deze onderzoekslijn …
Postdoc in Genetic Data Analysis
Project description Recent genome-wide studies have led to unprecedented progress in understanding the genetic architecture of brain-related traits and disorders, such as schizophrenia, depression, insomnia and intelligence. In this project we aim to advance our ...
- De Boelelaan, Amsterdam, Noord-Holland
- Tijdelijk contract / Tijdelijke opdracht
- Uren per week:
- 32 - 40 uur
- € 3111 - € 4757 per maand
Recent genome-wide studies have led to unprecedented progress in understanding the genetic architecture of brain-related traits and disorders, such as schizophrenia, depression, insomnia and intelligence. In this project we aim to advance our understanding of these results in biological context. We will develop and apply novel statistical and bioinformatic tools, and use new, biologically informative resources. Connecting the dots between different lines of evidence is the central theme in this project, aiming to advance insight into neurobiological pathways of neuro-cognitive traits, and generate testable hypotheses for functional follow-up experiments.
We are seeking a highly motivated, talented individual. You will be working with large genetic and genomic datasets, with information on brain related traits (e.g. cognition, schizophrenia, autism, mental retardation, neurodegenerative disorders), and subsequent bioinformatics annotation. We are looking for a candidate proficient in statistics and statistical programming, and preferably an understanding of principles of molecular genetics, and knowledge of e.g. chromatin interactions, gene expression, and epigenetics. Practical experience in the analysis of genomics data (e.g. expression data, GWAS, WGS, WES) is a pré.
For the Postdoc position we require a PhD in any of the of the following fields: bioinformatics, statistics, medical statistics, statistical genetics, computer programming, computational biology or related quantitative/computational field, and demonstrable experience in genetic data analysis.
In addition, we require a good ability to write and read English, experience working with large datasets, strong computer programming skills, and experience with the R statistical language and working in a UNIX environment.
The initial appointment will be for a period of 1 year. After satisfactory evaluation of the initial appointment, it will be extended for a total duration of
3 years (Postdoc). Information about our excellent fringe benefits of employment can be found at our website and include for example:
• Remuneration of 8,3% end-of-year bonus and 8% holiday allowance;
• Solid pension scheme (ABP);
• A minimum of 29 holidays in case of full-time employment;
The salary will be in accordance with university regulations for academic personnel, and ranges from a minimum of € 3111,00 and € 4757,00 (salaryscale 10/11, depending on experience) for a Postdoc.
For additional information please contact:
Prof.dr. D. Posthuma
phone +31 (0)20 59 82823
Vrije Universiteit Amsterdam (VU) is a leading, innovative and growing university that is at the heart of society and actively contributes to new developments in teaching and research. Our university has ten faculties, and provides work for over 4,500 staff and scientific education for more than 23,000 students.
The Complex Trait Genetics lab (http://www.ctglab.nl) at the Center for Neurogenomics and Cognitive Research in Amsterdam (see http://www.cncr.nl) is seeking applicants for a PhD or Postdoc position in Neuropsychiatric Genetics/Bioinformatics.
Research at the department of Complex Trait Genetics focuses on identifying the genetic and environmental causes of individual differences in human traits related to behavior, cognition and mental and physical health. We integrate knowledge from different fields (biology, genetics, neuroimaging, bioinformatics) and use and develop statistical and bioinformatics tools to analyze genome-wide data sets for complex traits.