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PRODID:-//Cancer Epigenetics Society - ECPv5.3.2.1//NONSGML v1.0//EN
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X-WR-CALNAME:Cancer Epigenetics Society
X-ORIGINAL-URL:https://ces.b2sg.org
X-WR-CALDESC:Events for Cancer Epigenetics Society
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DTSTART:20190331T010000
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DTSTART:20191027T010000
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DTSTART;VALUE=DATE:20190430
DTEND;VALUE=DATE:20190602
DTSTAMP:20260729T230005
CREATED:20190430T141117Z
LAST-MODIFIED:20190430T141117Z
UID:21221-1556582400-1559433599@ces.b2sg.org
SUMMARY:Senior Scientist- Informatics & Predictive Sciences
DESCRIPTION:We seek a talented\, collaborative computational researcher to drive the effort in multi-omics data integration and target evaluation/prioritization for solid tumor indications.\nThe successful applicant is expected to play a key scientific role in leveraging innovative computational analysis strategies across a variety of biological and chemical data sources to empower data-driven decisions in development of next generation Celgene protein homeostasis therapies for solid tumor indications. \nReporting to the Informatics Lead for Protein Homeostasis research\, the successful candidate will work alongside Celgene Research colleagues in the Protein Homeostasis Thematic Center of Excellence (TCoE) and Chemistry and Structural Biology based in San Diego California\, and the global Informatics & Predictive Sciences (IPS) department.  \nScientific objectives and research scenarios include: \n\nIntegrating data across internal and public datasets for new target identification\, prioritization and indication selection\,\ndeveloping systems biology approaches for assessing disease relevance and generating therapeutic hypothesis on novel targets\,\nearly identification and predictive leverage of patient molecular subtypes most likely to benefit from a targeted intervention\,\ninference of synergistic target combinations by leveraging pharmacogenomics data and molecular networks.\n\n\nData originate from a wide range of cellular and molecular profiling platforms\, including transcriptomic\, proteomic\, genomic\, functional and immunophenotypic assays\, and from the efforts of colleagues in structural biology and cheminformatics.\nThe role offers the opportunity to directly impact the delivery of transformational therapies in key diseases of unmet medical need. Strong interest in the inter-disciplinary application of computational analysis methods to life sciences data is imperative. \nResponsibilities \nWorking in collaboration with computational\, biological and drug discovery scientists across the Celgene Research and Development organization\, responsibilities include but are not limited to:  \n\nAccelerate cutting edge predictive computational research in drug discovery utilizing new technologies\, model systems and the power of AI.\nDevelop and apply innovative computational analysis to leverage internal\, public and partner datasets and empower data-driven decisions for new target prioritization and validation.\nLead the identification and systematic ingestion of publicly available cancer genomics and relevant annotation and literature datasets\, and their integration with internal data sources.\nCollaborate as a member of cross functional teams to drive rational decision making across early drug discovery programs.\nAuthor scientific reports\, and present methods\, results and conclusions to publishable standard.\nContribute to planning and execution of collaborative projects with leading academic and commercial research groups worldwide.\n\n\nBackground experience & complementary knowledge  \n\nPh.D. in computational biology\, bioinformatics\, or related field from a recognized higher-education establishment.\n6+ years of experience in applying quantitative approaches to solve biological problems in university\, hospital\, pharma or biotech research environments\, with considerable depth of experience in cancer genomics.\nDemonstrated ability to integrate heterogeneous data sources and perform multivariate analysis of integrated datasets.\nProven expertise in the development and/or implementation of algorithms to distill\, analyze and interpret complex datasets\, with focus on evidence integration and mechanistic inference.\nExperience of computational biology research on a wide variety of molecular profiling platforms\, including mRNA profiling\, mutational profiling\, DNA copy number quantification\, epigenetic profiling and proteomics.\nFamiliar with various cancer genomics consortium efforts\, tools and databases.\nExpertise in algorithmic implementation\, statistical programming and data manipulation\, using e.g. R/Bioconductor and contemporary\, open-source bioinformatics tools and database structures.\nTrack record of peer-reviewed publications in top-tier scientific journals.\nProven problem-solving skills\, collaborative nature and adaptability across disciplines.\nExcellent verbal and written communication skills. Fluent verbal and written English language skills prerequisite.
URL:https://ces.b2sg.org/event/30apr19/
LOCATION:Celgene San Diego\, 10300 Campus Point Dr\, San Diego\, CA\, 92121\, United States
CATEGORIES:Jobs
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