Postdoctoral Fellow - Human Population Genetics Research
This amazing opportunity is located in Iceland - Reykjavík, relocation will be offered.
deCODE Genetics is searching for highly-qualified and motivated post-doctoral fellows in the fields of Computer Science, Mathematics, Biostatistics, Bioinformatics, Artificial Intelligence, Biomedical Engineering, Electrical Engineering and Statistical Genetics. This is a rare opportunity to conduct cutting-edge human population genetics research in an environment that combines the benefits of academia and industry. Post-doctoral fellows will be mentored by Dr. Kári Stefánsson and other deCODE scientific leaders. Opportunities will be available to initiate and/or participate in publications in highly-regarded journals.
The tenure for these competitive fellowships is 3-years with the option to renew for an additional year.
Current graduates and graduate students nearing completion of their doctoral studies are welcome to apply. Immigration and relocation assistance will be provided. The working language at deCODE is English.
- Post-doctoral fellows will be tasked with various projects related to human population genetics
- Analyzing the relationship between plasma protein levels and disease (proteomics)
- Analyzing carriers of predicted high impact loss of function variants and identifying common phenotypic traits
- Developing methodology, algorithms and software for the joint analysis of RNA, proteomics, methylation and DNA data
- Developing efficient algorithms and software for analysis of long read and short read DNA data, including assembly algorithms
- Developing methodology, algorithms and software for the analysis of RNA-Seq datasets with a primary emphasis on association with genetic variants and disease phenotypes
- Using machine/deep learning to extract new phenotypes from imaging data
- Developing algorithms and software to work with large datasets and reduce computational resources
deCODE Genetics, a wholly-owned subsidiary of Amgen, is a global leader in analyzing and understanding the human genome. Under the leadership of founder and CEO Dr. Kári Stefánsson, deCODE has used its unique expertise and population resources to discover key genetic risk factors for dozens of common diseases ranging from cardiovascular disease to cancer. deCODE has collected one of the world’s largest integrated datasets on genetic variation, WGS, RNA, proteomics and associated large-scale phenotypic data. Prior to founding deCODE, Dr. Stefánsson held professorship and leadership positions at several institutions including Harvard University. He and several deCODE researchers are current faculty at the University of Iceland. In 2019, Dr. Stefánsson was elected as a foreign associate of the US National Academy of Sciences.
Basic Technical Qualifications
- Ph.D. in Mathematics, Biostatistics, Statistical Genetics, Bioinformatics, Computer Science, Artificial Intelligence or similar field
- Strong algorithmic background
- Proficiency in C++ and Python
- Experience in working with large datasets, GPU programming, and statistical methods
- Experience in working with RNA, methylation, proteomics, or sequencing data
- Demonstrated expertise in relevant analytical subfields. These include but are not limited to: neural networks, probabilistic graphical models (e.g. Bayesian networks), and network representations of data (e.g. topological data analysis)
- Track record of publishing