The Scripps Research Institute is currently seeking a computational Postdoc for the Andersen Lab working in the Department of Immunology and Microbiology. The successful candidate will join an interdisciplinary team of scientists, biologists, clinicians, and computational scientists to apply computational tools to advance the state of the art in quantitative infectious disease research. We are looking for a dedicated individual who will help us transform medicine with a direct impact on global health.
The Andersen lab is working on diverse projects using computational genomics approaches and high-throughput experiments to study emerging viruses and the outbreaks the cause, including Lassa, Ebola, West Nile, and Zika. We use an integrated approach of fieldwork in West Africa, technology development, and computational biology to investigate these viruses.
We are looking for a computational postdoc to lead new projects developing and using data mining, machine learning and Bayesian phylodynamic approaches to investigate the spread and evolution of emerging viruses, including Lassa and Ebola. This position is part of a larger initiative with the recently established Center for Viral Systems Biology (https://cvisb.org/).
Tasks will include:
- Develop novel data mining strategies and deploy computational tools for the exploration of large biological data sets.
- Perform independent research exploring the utility and applications of next-generation sequencing in a global health setting.
- Develop and implement statistical models; work with wet-lab researchers to translate these models into testable experiments; analyze the data produced from these experiments.
- For interested candidates, fieldwork in Sierra Leone is also a possibility.
- Programming skills in two or more languages (C++/Java/Python/R/MATLAB).
- Deep knowledge of Bayesian statistics, in particular Bayesian phylogenetics is a big plus.
- Strong interpersonal skills and the ability to work with and mentor junior scientists and students.
- Ph.D. in computational biology, computer science, mathematics, physics, or equivalent.
- Experience with data mining and machine learning is highly desired.
- Data visualization in Python/R/d3js is a plus.
- Experience with HPC preferred.