Scientist, Research Data

Research, Innovation & Impact (RII) Core Facilities at the University of Arizona invites applications for an Research Data Scientist (Data Scientist III) for its Analytical and Biological Mass Spectrometry (ABMS) Core. The ABMS Core provides a variety of mass spectrometry services in a well-equipped university-wide facility. The successful candidate will be primarily responsible for providing high-level bioinformatics for proteomics and metabolomics research projects, small molecule analysis, and quantitation to both the University of Arizona and external researchers. The successful candidate will be involved in consulting with researchers along with the core director/manager, and is expected to participate in experimental design, sample preparation, LC-MS/MS analysis, data analysis, interpretation, and bioinformatics. The candidate will be expected to assist the manager in the day-to-day operation of the Core. This position will report to the manager of the facility. The ideal candidate for this position will model the highest degree of professionalism, as demonstrated in their work ethic and interpersonal engagement with colleagues. They will be a self-starter who takes initiative to master new skills and content areas to continually improve in the position. We are looking for someone who can do well in a team environment, communicate effectively, and work independently on assigned tasks to advance the larger research mission of the University.

Research, Innovation & Impact (RII) supports world-class research and discovery by University of Arizona faculty, staff, and students with particular attention to the University's land-grant mission of service to the State of Arizona. RII enables the research success of University of Arizona faculty through its support of University research centers, institutes, museums, and core facilities; provision of research development, compliance and safety services; and strategic external partnerships. The University of Arizona seeks to build on its great strengths in interdisciplinary research by expanding its fundraising program dedicated to securing philanthropic support for interdisciplinary campus-wide initiatives that cross multiple academic interests.

The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.

Duties & responsibilities:

• Data
  processing and bioinformatics analysis of Proteomic, Metabolomics and
  Small Molecule quantitation projects with vender specific proteomic data
  analysis software platforms, as well as third-party software platforms
  such as Proteome Discoverer, Compound Discoverer, TraceFinder, Lipid
  Search, MASCOT, Max Quant, Byonic, Skyline, and Scaffold.
• Analyzes
  small molecules using Bruker solariX FTICR, QExacitve Plus, Orbitrap
  Exploris 480, and an ALTIS triple-quadrupole mass spectrometers.
• Receives
  direction from the Manager to address major research goals of the lab.
  Uses knowledge and technical expertise in sample preparation,
  separation, and analysis by mass spectrometry and data processing to
  complete research projects.
• Summarizes
  data analyses results in the form suitable as the basis for the first
  draft of written reports, and makes preliminary interpretations of the
  data.
• Manages data including loading
  and querying data from database systems, downloading -omics data from
  public repositories, and transforming data to the necessary formats.
• Helps
  to identify, evaluate, and incorporate relevant algorithms and software
  pipelines by reviewing pertinent literatures in bioinformatics and
  computational biology.
• Attends
  weekly team meetings to discuss results, plan experiments to ensure
  that projects support current team goals in a dynamic environment.
• Assist
  in the operation and routine maintenance of analytical instrumentation
  including other mass spectrometers in the facility.
• Additional duties may be assigned.

Knowledge, skills & abilities:

• Excellent
  interpersonal and oral/written skills to interact with a diverse group
  of graduate and undergraduate students, staff, faculty, and visitors.
• Basic understanding of the theory and practice of mass spectrometry.
• Strong
  computer skills with the concepts and practices of the field of
  Bioinformatics as it relates to mass spectrometry and experience with
  MS-based Omics data analysis systems and software.
• Knowledge
  of MS software (Thermo, Bruker), database search and evaluation
  software (MASCOT, MaxQuant, Perseus, Proteome Discoverer, PEAKS,
  Spectronaut, Scaffold), and associated bioinformatics tools (R, Python)
  is advantageous.
• Open-minded and motivated personality with a focus on team play.
• Knowledge
  of MS software and evaluation software (Proteome Discoverer, PEAKS,
  MASCOT, Scaffold) and associated bioinformatics tools (R, Python) is
  advantageous.
• Excellent knowledge of written and spoken English.
• Excellent written and verbal data presentation skills and the ability to use software tools to produce high-impact presentations of data, highlighting key takeaways.
• Detail-oriented with the ability to capture and record complex scientific data accurately and reliably.

• Master's degree in Computer Science, Electric Engineering, Computational biology, or Bioinformatics, or relevant fields (e.g. Biology, Chemistry, Biochemistry, Analytical Sciences with strong quantitative training, biostatistics with concentration in bioinformatics).
• Minimum of 5 years of relevant work experience.

• Experience in a research environment.
• Experience working in algorithms, scientific computing, and machine learning or statistics.
• Experience with R software, C/C++, Java, Perl, python, and the Unix (Linux) environment.
• Experiences in manipulating, analyzing, and annotating very large -omics data sets, both in exploratory and pipelined fashions, will be a plus.
• Experience in small molecule characterization and quantitation using Mass Spectrometry is a plus but not required.
• Experience in R programming is a plus.
• Experience with programming platforms such as R (R Studio) and other informatics tools such as MS Stats is a plus.