Senior / Staff Scientist, Bioinformatics - Life Technologies (Silicon Valley/Peninsula, California)

Making Life Even Better
When it comes to the vision of shaping discovery and improving life, no other company can match the breadth of products and services in the life sciences field to meet this vision than Life Technologies. Created through the combination of biotechnology leaders Applied Biosystems and Invitrogen, Life Technologies systems, consumables and services enable researchers to accelerate scientific exploration, driving to discoveries and developments that improve the human condition and the world around us. Our customers do their work across the biological spectrum, working to advance personalized medicine, regenerative science, molecular diagnostics, agricultural and environmental research, and 21st century forensics. With historical sales of approximately $3.5 billion, a presence in more than 100 countries, and a rapidly growing intellectual property estate of over 3,600 patents and exclusive licenses, we are poised to truly shape the world of science. Join a team of more than 9,500 employees around the world who are engaged, curious, insightful, responsible and driven to make life even better.

Major Responsibilities:

We are seeking to recruit a computational biologist/statistical geneticist to contribute to analysis projects with our next-generation, ultra high-throughput sequencing platforms. This individual will develop and apply statistical methods and tools to solve highly complex scientific problems involving statistical genetics and genomics. Working closely with customers and collaborators, the candidate will be responsible for developing analysis strategies for diverse applications, such as genome and transcriptome sequencing, DNA binding factor analysis, medical resequencing, and structural variation profiling studies. This individual will regularly interact with academic and industrial researchers and their teams in collaborative projects, developing new experimental and analysis strategies. The candidate will be key contributor to efforts in integrate and analyze a diversity of data, including genotype data, population data, clinical phenotype data, sequence data, and gene expression data as the projects require. Through interactions with members of the bioinformatics, product development, and application sequencing teams, the candidate will keep up to date with the latest platform development status, experimental protocols, and the necessary tools and software needed to process the data. Other responsibilities include presentations at scientific meetings, keeping abreast of the latest developments in genomics and statistical genetics, timely publication of research and development findings, and maintaining external contacts.



Skills/Knowledge Requirements:

The interdisciplinary nature of the position requires a solid foundation in both biology and informatics/statistics. This position requires the knowledge and skills normally acquired through completion of a PhD degree in Computational Biology, Applied Mathematics, Computer Science, Statistical Genetics, Molecular Biology, or related field, with at least 3 years of relevant experience in statistical genetics, genetic epidemiology, sequence analysis, or gene expression profiling data analysis. Your statistical expertise includes hands-on experience with one, and preferably more of: linkage analysis, linkage disequilibrium mapping, association studies, multivariate statistics, population genetics (e.g. coalescent simulations), data mining, and microarray data analysis. Additionally, candidates will be expected to demonstrate the ability to work in a UNIX/Linux environment and be proficient with a scripting language (e.g. Perl/Phyton) and/or software programming languages (e.g. C/C++/Java), and have experience on the use of common statistical, data mining, and visualization tools (e.g. SAS, S-Plus, R, MatLab) in the interpretation of biological data. The successful candidate must be self-motivated and capable of working both independently and within a closely interacting team of scientist in an international collaborative environment. She/he should be comfortable with detail-orientated work, project deadlines and the challenges and excitement associated with working in a fast moving field. Previous experience with data from new genomics technologies, especially next generation sequencing and dense microarrays, and its integration, is highly desirable. Good communication and organization skills are essential, as well as a record of scientific contributions/publications. Previous biotech/industry jobs, database or algorithm development experience, project management skills, and a record of leading or supervising technical/scientific professionals, are pluses.

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