Staff Astronomer I

Key Responsibilities

Support of Visiting Astronomers (Observers)

• Instruct observers in the use of WMKO’s instruments and telescopes
• Provide pre- and post-observing inquiries and support (both onsite and at remote mainland sites).
• Offer afternoon and night-time support for observers during their runs.

Instrumentation Maintenance and Development

• Maintain, calibrate, and develop scientific instruments and related software.
• Provide night-time engineering support.
• Collaborate with engineers and technicians to maintain, repair, and improve instruments.

Instrument Scientist (when assigned) Responsibilities

• Lead the care of that instrument or capability.
• Take primary responsibility for the instrument, ensuring its proper function and performance.

Contributions to New Instrumentation and Upgrades

• Participate in the development of new instruments or capabilities, including adaptive optics.
• Contribute to major upgrades of existing instruments

 Data Reduction Support

• Contribute to the development, maintenance, and support of data reduction packages.

Research

• Conduct scientific research related to field of expertise or interest with the expectation that the research will lead to published technical and peer-reviewed papers. Collaboration with colleagues is encouraged.
• This position allocates 20% of work time specifically for research activities. 

Skills, Knowledge and Expertise

Education

• Doctor of Philosophy (Ph.D.) or equivalent degree in astronomy, physics, or engineering; relevant professional experience may be substituted for a degree.

Experience

• Interest and/or experience with scientific instrumentation
• With astronomical observing and/or working at an astronomical observatory.

Skills

• Ability to prioritize tasks, plan activities, and meet deadlines
• Microsoft Office Proficiency.
• Ability to effectively deliver impactful presentations to a technical and non-technical audience. 

Technical Competencies

• Ability to interpret complex data, solve problems, and make predictions based on empirical evidence.
• Proficiency in programming languages for data analysis and simulations (e.g., Python, C/C++, IDL, R, Bash/Shell scripting).
• Ability to create or use data processing pipelines to handle large volumes of data, including calibration, cleaning, and extraction of useful information.
• Knowledge of cloud computing and data storage solutions to manage large datasets.
• Ability to write scientific papers and produce technical documentation. 

Applications will be reviewed until a suitable candidate is found.