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美国洛杉矶Genentech Research的博士后研究员,基因组学与生物信息学Manning实验室

2018-04-16 21:21 来源: 互联网转载 作者: liuxuehr

Postdoctoral Position in Genomics and Bioinformatics (Manning group)

Cancer is a complex, resilient disease, and a continuing scourge of humanity. Cancer is also a genomic disease, and the key to understanding and defeating it is understanding the diverse genomic strategies that drive cancer. The first generation of cancer genomics delivered ‘things’ – mutations, amplifications, fusions, expression profiles etc. We’re looking for an ambitious postdoc to help us understand the next generation of cancer genomics – the patterns of genomic changes that will reveal the molecular strategies used by tumors, and uncover new therapeutic possibilities.

We have access to genomic profiling of over 150,000 tumors from public and private sources, working within a leading bioinformatics department embedded in probably the world’s most successful cancer drug development organization. This is a unique opportunity to drive cancer genomics to the next level of understanding, and to enable this understanding to be deployed for real patient benefit.

The primary goal of postdocs is scientific discovery and publication (see http://www.gene.com/careers/academic-programs/postdocs), and the program is geared towards developing future independent investigators.

The Department of Bioinformatics and Computational Biology at Genentech is one of the largest bioinformatics research groups with a remarkable breadth and depth of expertise, a strong team environment, deep links to our research colleagues, and a uniquely strong opportunity to help develop breakthrough new medicines. The Manning lab (http://manninglab.org; https://www.gene.com/scientists/our-scientists/gerard-manning) focuses on understanding of biological function and disease through deep genomic analysis.

Who You Are

Candidates for this position should have:

A PhD plus a strong background in bioinformatics and genomics and a broad understanding of cancer and cancer genomics. Knowledge of cell biology, protein structure, biochemistry or signaling a plus.

Robust mathematical and statistical skills, and a track record of applying them to complex and noisy biological data. Experience in computational modeling and machine learning a strong plus.

Proficiency in R programming and experience in standard bioinformatics toolkits and programs.

Strong communication and teamwork skills to take advantage of our highly collaborative environment, working with both computational and experimental scientists.

A passion for innovation, and demonstrated initiative and track record in tackling new areas of research.

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