Scientific Data Engineer

3 weeks ago

Durham, United States GAP Solutions, Inc. (GAPSI) Full time

Position Objective: Provide services as a Scientific Data Engineer in support of the overall functions of the National Institute of Environmental Health Sciences (NIEHS) within the National Institutes of Health (NIH). The Predictive Toxicology Branch of the National Institute of Environmental Health Sciences (NIEHS) is seeking an individual to develop methods and software for novel predictive models, including artificial intelligence (AI) and machine learning (ML) applications. This position will work across the Division of Translational Toxicology (DTT) to synthesize toxicoinformatic, spatiotemporal, dose-response, and systems toxicology data sources.

Duties and Responsibilities:

  • Generate and optimize programs and scripts for the analysis of data; create programs and algorithms and develop computational infrastructure resources for organizing and parsing data from large and complex data.
  • Serve as bioinformatics expert and coordinate with teams of biologists to conduct experimental queries and/or perform portions of studies using complex procedures and techniques common to modern bioinformatics.
  • Coordinate building bioinformatics infrastructure to ensure easy and meaningful scientific analysis and interpretation of data. 1
  • Provide interpretive analyses of data derived from different experimental platforms to generate biological meaning.
  • Collaborate with scientists to design, analyze, manage and interpret all types of data. 2
  • Work with staff on planning of experiments, and data analysis for internal and collaborative projects; use bioinformatics expertise to advise and help bench scientists on experimental design and trouble-shooting. 3
  • Prepare scientific reports and progress reports; assemble data to prepare tables, graphs and slides; conduct scientific and program related information searches and report results.
  • Devise novel methods of statistical analysis for collected data.
  • Develop and optimize programs and scripts that facilitate organization, integration and data-mining of large data sets; integrate these models into a framework of best practices.
  • Work with staff on the development and maintenance of bioinformatics tools, scripts and pipe-lines for data. 4
  • Identify new tools and resources for reaching biologically meaningful conclusions.
  • Provide training in and technical support (including product updates and version control) for programs, algorithms, archives, and pipelines generated during the course of this work.
  • Provide ad hoc trainings and hands-on workshops on the use of bioinformatics tools.
  • Work with an interdisciplinary team to apply computational data analysis approaches to make biological discoveries.
  • Collaborate with biologists, statisticians and/or other bioinformaticians in the design of models summarizing/explaining experimental data. 5
  • Attend group meetings; present findings; author publications resulting from projects.
  • Present analysis results at research conferences and meetings.
  • Present scientific and technical data at scientific conferences.
  • Facilitate implementation of software tools to be used by the entire Division. - Ad-Hoc
  • Build and maintain a repository of shared code for new and ongoing projects. Quarterly
  • Contribute to team-science publications that describe new modeling applications. - Yearly

Basic Qualifications:

  • Masters degree in Information Sciences, Computer Programming and Data Processing, Mathematics, or a related discipline.
  • Bioinformatics training required.
  • Skilled in Linux, Java, CSS, Javascript, ArcGIS, PHP, R, Bash, GitHub, and Python.
  • Experience working with large data sets.
  • Experienced with pipeline development, data quality control, data harmonization, algorithm development, statistical modeling, data cleaning, data analysis, research, clinical and/or translational research, and machine learning.

Minimum Qualifications:

  • Ability to multi-task and pay close attention to detail.
  • Excellent analytical, organizational and time management skills.
  • Strong communication skills, both oral and written.

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