Sr. Bioinformatics Scientist - Computational Model
Overview: The Senior Bioinformatics Scientist - Computational Modeling and Pathway Analysis will lead numerical algorithm and gene network analysis for biomarker discovery. The candidate should be experienced with numerical programming in C/C++, Matlab, and/or R. Experience applying principles of pattern recognition and machine learning to modeling biological systems within a Linux-based, high performance computing (HPC) environment. Specific modeling frameworks would include graphical models (Bayesian or Markov), mixture models, adaptive pattern classifiers and kernel methods. Familiarity with techniques such as sampling or variational methods, factor graphs, the EM algorithm, neural networks, vector machines, principal component analysis, matrix factorization methods, shrinkage methods and boosting/regularization. Demonstrate understanding of the numerical stability and statistical issues that can arise during the analysis of high dimensional datasets. The Senior Bioinformatics Scientist position requires an advanced degree in physics, engineering, mathematics, bioinformatics, computer science, or related technical field. Genomics and biotech experience is desirable but not required. This position will interact with the teams in Research, Development, and Information Technology departments. Good oral and written communication skills are required. Responsibilities: Develop computational algorithms and programs for identification of gene networks aimed at cancer biomarker discovery. Implement and optimize open source or third party numerical programs for gene network computing. Evaluate various network modeling methods for cancer biomarker discovery. Participate in cancer genomics research. Develop intellectual property on innovative computational methods for genomics applications. Publish scientific papers.
Redwood City, CA
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