BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Cancer Epigenetics Society - ECPv5.3.2.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Cancer Epigenetics Society
X-ORIGINAL-URL:https://ces.b2sg.org
X-WR-CALDESC:Events for Cancer Epigenetics Society
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20170326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20171029T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20170722
DTEND;VALUE=DATE:20170823
DTSTAMP:20260730T124143
CREATED:20170722T092543Z
LAST-MODIFIED:20170722T092623Z
UID:18855-1500681600-1503446399@ces.b2sg.org
SUMMARY:Postdoc Research Associate
DESCRIPTION:A Lineberger Comprehensive Cancer Center Research Laboratory aims to understand the pathogenesis and pharmacogenomics of pancreatic cancer in order to accelerate its treatment. Using a combination of molecular and genomic data\, and human in mouse models\, we have identified four core subtypes in pancreatic cancer with important biologic and clinical implications. We are seeking a postdoctoral associate in cancer genomics and personalized medicine who will be responsible for computational method development\, data analysis\, and experimental design. The qualified candidate will integrate information from a combination of sources\, including high throughput screens\, proteomic\, and next-gen sequencing data in order to generate and validate hypotheses of therapeutic relevance to pancreatic cancer. The ideal candidate will have excellent qualifications in a quantitative/computational field with a strong interest in learning cancer biology and/or wet bench techniques. Candidates from a largely wet bench background with a Ph.D. may be considered if the quantitative/computational background is excellent.   \nTo be successful\, the candidate must have experience in and interested in developing several of the following skill-sets: -Thorough knowledge of cancer biology\, epigenetics\, proteomics\, and transcriptomics -Familiarity with next-generation sequencing data analysis tools -Experience working in Linux environments\, including batch job management on shared computing resources -Familiarity with a variety of supervised and unsupervised classification techniques -Proficiency in one or more statistical or scripting languages\, preferably R or MATLAB -Knowledge of survival-based statistical analysis\, e.g. Cox regression and Kaplan-Meier analysis -Working knowledge of best-practices for machine learning to avoid over fitting -Familiarity with common experimental techniques in molecular biology -Ability to communicate scientific material and collaborate well with computational and non-computational partners -Excellent oral and written communication skills and the ability to perform both self-directed and guided research -Outstanding personal initiative and the ability to work effectively as part of a team -Willingness to assist in the mentorship and training of pre-doctoral researchers Ph.D. in a quantitative/computational field or a Ph.D. with an equivalent certificate in a quantitative/computational field is required. -Have experience in handling large datasets and have applied/developed computational algorithms in the context of molecular biology. -Have a thorough understanding of common statistical tests and distributions.  \nBe able to collaborate with experimental team members for validation of computational results. -Be comfortable maintaining datasets\, as well as displaying and interpreting processed data for publication. -Work alongside domain experts in the optimization and development of experimental measurement platforms and protocols.   \n 
URL:https://ces.b2sg.org/event/unc-postdoc-jul17/
LOCATION:University of North Carolina – UNC-Chapel Hill\, Chapel Hill\, NC\, United States
CATEGORIES:Jobs
ATTACH;FMTTYPE=image/png:https://ces.b2sg.org/wp-content/uploads/2016/07/U_North_Carolina-2.png
END:VEVENT
END:VCALENDAR