Job Description:
We are seeking a postdoc to lead the development and application of new computational methods to large-scale single-cell sequencing datasets. You: You must be an independent, motivated, creative and enthusiastic individual with a background in bioinformatics, computer science, computational biology, or other relevant quantitative disciplines (statistics, engineering, physics and math preferred). You should be comfortable applying your technical skills to a new, exciting and ever-changing field by developing efficient and scalable software tools and partake in the analysis of primary data. A general interest in making fundamental discoveries of how our genomes encode biological function would be helpful. You must be able to interact with experts in other disciplines such as immunology, molecular biology and clinical sciences. Qualifications :
Additional Info:
Us : The Yelab are a dynamic team based in the Institute for Human Genetics and the Institute for Computational Health Sciences at UCSF. We are focused on developing computational and experimental approaches to better understand how our genomes encode biological function. We collaborate heavily with technologists to adapt new techniques to generate large-scale population genomics datasets such as RNA-seq and ATAC-seq in bulk and single cells to study human biology with a quantitative emphasis. We have three major goals in our lab: 1) to discover genetic polymorphisms and epigenetic marks responsible for phenotypic diversity such as disease susceptibility and differential vaccine response, 2) to develop computational models based on a combination of primary data analysis and biological insights to map transcriptional regulatory circuitry, and 3) to build software tools and infrastructures to collect, analyze and share genomic datasets. [Click Here to Access the Original Job Post]
We are seeking a postdoc to lead the development and application of new computational methods to large-scale single-cell sequencing datasets. You: You must be an independent, motivated, creative and enthusiastic individual with a background in bioinformatics, computer science, computational biology, or other relevant quantitative disciplines (statistics, engineering, physics and math preferred). You should be comfortable applying your technical skills to a new, exciting and ever-changing field by developing efficient and scalable software tools and partake in the analysis of primary data. A general interest in making fundamental discoveries of how our genomes encode biological function would be helpful. You must be able to interact with experts in other disciplines such as immunology, molecular biology and clinical sciences. Qualifications :
- PhD in bioinformatics, computer science, computational biology, physics, mathematics, statistical genetics or relevant field.
- Demonstrated previous research experience through at least one first-author publication in a reputable journal.
- Proficiency in programming (C/C++), scripting (perl/python) and statistical analysis (R).
- Comfortable handling > 1T of data
Requeriments :
Skills :
- immunology
- molecular biology
- Programing in C
- Programing in C++
- Programing in Python
- Programing Skills
- Programming in PERL
- Programming in R
Areas :
Additional Info:
Us : The Yelab are a dynamic team based in the Institute for Human Genetics and the Institute for Computational Health Sciences at UCSF. We are focused on developing computational and experimental approaches to better understand how our genomes encode biological function. We collaborate heavily with technologists to adapt new techniques to generate large-scale population genomics datasets such as RNA-seq and ATAC-seq in bulk and single cells to study human biology with a quantitative emphasis. We have three major goals in our lab: 1) to discover genetic polymorphisms and epigenetic marks responsible for phenotypic diversity such as disease susceptibility and differential vaccine response, 2) to develop computational models based on a combination of primary data analysis and biological insights to map transcriptional regulatory circuitry, and 3) to build software tools and infrastructures to collect, analyze and share genomic datasets. [Click Here to Access the Original Job Post]