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Computational Biologist


Employer: GlaxoSmithKline (GSK)
Location:
Posted: June 13, 2014
Expires: July 31, 2014
Requisition number:

Science jobs from GlaxoSmithKline (GSK) :
h2. Computational Biologist - GSK (Requisition Number: 99907)

Philadelphia, PA

The Computational Biology Department supports Drug Discovery and Development through the integrative analysis of internal and external biomedical data, combining strong computational skills with biological insight. Our analysis competencies are quite diverse, spanning areas such as data mining, drug repositioning, disease indications, microbiome/host pathogen analysis, omics data, comparative genomics, pathways and networks, molecular evolution, text mining, and business opportunities. We contribute to projects at all phases of the pipeline from initial target discovery through clinical phases and launched products. We also develop our own data-driven hypothesis and have them tested experimentally. Our work results in real impact on new medicines for highly important diseases of unmet medical need. Our group presents and organizes workshops at top bioinformatics and drug discovery conferences, and publishes high-impact papers.

Job Details

The GSK Computational Biology Department is seeking talented and motivated computational biologists to analyze complex internal and external data to help find cures for disease. As a Computational Biologist you will have a strong technical background in bioinformatics / computational biology / computer science allied with an excellent knowledge of biology. Your primary role will be to identify, invent, develop, implement and/or use computational biology methods to impact drug discovery and development. You will be comfortable with working in a dynamic, fast changing environment, and able to communicate complex informatics principles, methods, analyses and results to scientists from diverse backgrounds. You will be expected to maintain and develop appropriate computational biology skills, as well as, your internal and external scientific profile through presentations and peer-reviewed publications.

Preferred qualifications: PhD in bioinformatics / computational science / biomedical engineering/ biological sciences or equivalent research experience. Desirable to have knowledge of biological mechanisms and application of computational biology methods to impact drug discovery and development Demonstrated skills to programmatically collect, combine, mine and analyze complex biological data. Demonstrated skills in the analysis of multiple large scale genomic and genetic platforms such as transcriptomics, proteomics and DNA sequencing (including NextGen sequencing). Publication record in peer reviewed journals Strong communication skills, both written and oral * Ability to work effectively in multidisciplinary teams and communicate clearly complex results of computational analyses and concepts to influence diverse audiences

Some recent publications by GSK Computational Biology:

# Smith SB, Magid-Slav M, Brown JR. 2013. Host response to respiratory bacterial pathogens as identified by integrated analysis of human gene expression data. PLoS One. 2013 Sep 27;8(9):e75607 # Agarwal P, Sanseau P, Cardon LR. 2013. Novelty in the target landscape of the pharmaceutical industry. Nat Rev Drug Discov. 2013 Aug;12(8):575-6. # Rajpal DK, and Brown JR. 2013: Modulating the human gut microbiome as an emerging therapeutic paradigm. Sci Prog. 2013;96(Pt 3):224-36. # Freudenberg JM, Rajpal N, Way JM, Magid-Slav M, Rajpal DK. 2013: Gastrointestinal weight-loss surgery: glimpses at the molecular level. Drug Discov Today. 2013 Jul;18(13-14):625-36. # Hurle MR, Yang L, Xie Q, Rajpal DK, Sanseau P, Agarwal P. 2013. Computational drug repositioning: from data to therapeutics. Clin Pharmacol Ther. 2013 Apr; 93(4):335-41. # Cheng J, Xie Q, Kumar V, Hurle M, Freudenberg JM, Yang L, Agarwal P. 2013: Evaluation of analytical methods for connectivity map data. Pac Symp Biocomput. 2013:5-16. # Sanseau P, Agarwal P, Barnes MR, Pastinen T, Richards JB, Cardon LR, Mooser V. 2012. Use of genome-wide association studies for drug repositioning. Nat Biotechnol. 2012 Apr 10;30(4):317-20 # Vavro C, Hasan S, Madsen H, Horton J, DeAnda F, Martin-Carpenter L, Sato A, Cuffe R, Chen S, Underwood M, Nichols G. 2013. Prevalent polymorphisms in wild-type HIV-1 integrase are unlikely to engender drug resistance to dolutegravir (S/GSK1349572). Antimicrobial Agents Chemotherapy: 57(3):1379-84 # Smith SB, Dampier W, Tozeren A, Brown JR, Magid-Slav M. 2012. Identification of common biological pathways and drug targets across multiple respiratory viruses based on human host gene expression analysis. PLoS One. 2012;7(3):e33174. # Qu XA, Rajpal DK, 2012. Applications of Connectivity Map in drug discovery and development. Drug Discov Today. 2012 Dec;17(23-24):1289-98 # Collison M, Hirt RP, Wipat A, Nakjang S, Sanseau P, Brown JR. 2012. Data mining the human gut microbiota for therapeutic targets. Briefings in Bioinformatics. 2012 Nov;13(6):751-68

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