104 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions at Fred Hutchinson Cancer Center
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
analyzing the data. They will interpret and report on experimental results and assist with data presentation. They will assist in writing laboratory SOPs, reports, and other documentation. They will report to
-
, information seeking, logical reasoning, predicting, and transforming knowledge Ability to develop clinical judgment. Time Management skills: the ability to organize and manage time and tasks independently
-
use of multiple computer systems. This position is full-time, hourly. Location is onsite at our South Lake Union campus, and travel required to imaging van locations. Responsibilities Schedules all
-
be responsible for performing and coordinating the assays with other technicians and analyzing the data. They will interpret and report on experimental results and assist with data presentation
-
(multi-site, sub awards etc.). Develop, run and analyze reports to identify issues and develop recommendations. Develop customized report formats to share information with broad audiences across
-
facility abstracting coding (ICD9,ICD10, HCPCS and CPT) and facility coding modifiers. Experience may be substituted for a Bachelor's degree in Health Informatics or Health Information Management along with
-
discoveries and treatment options for patients with rare and understudied cancers. We work closely with scientists, clinicians, patients, and advocates to drive data-sharing, drug repurposing, and innovative
-
viewpoint. Demonstrates good customer relations skills. Demonstrated leadership skills. Proficiency in use of standard office computer software programs, equipment and clinical information systems. Preferred
-
publication of results by proofreading, editing, and contributing ideas. May perform statistical analyses, write computer programs, or manage research database. Assist in general lab maintenance and tasks
-
questions in biomedical sciences and abundant information in big genomic and health related data. On the statistical methodology side, our example interests include association measures, high-dimensional