Job Summary
Research Assistant I or II, depending on applicant’s background and experience (Temporary: August 5, 2024 – Sep 30, 2025)
Successful candidates will provide professional consultation and hands-on support for data science, data quality control, data processing, scientific data analysis and visualization, data management, and database maintenance to a group of PIs in the Physical Oceanography and the Applied Ocean Physics and Engineering Departments at WHOI. Projects cover climate variability and change, regional oceanography, and ecosystem impacts. Responsibilities include implementing data pipelines and computational workflow and guiding students and researchers on data workflow design plans and protocols for maintenance and management of data sets through all phases of research; review progress and assure accuracy and compliance of data being acquired and stored; computational research support to implement approaches to helping streamline and improve coding efficiency.
Essential Functions
Individuals in this position are expected to possess the necessary skills to acquire data from various sources; clean, merge, and organize complex data across multiple projects; improve coding efficiency; and create data visualizations. Ideal candidates will have practical experience in organizing large datasets within a Linux environment, often requiring parallel processing (e.g., dask), processing large multi-dimensional observational, and reanalysis datasets, and global climate models. Additionally, proficiency in common programming environments such as python, Matlab, or R is essential. Experience with coding collaboration solutions (e.g., GitHub), columnar data types, and cloud services (i.e. AWS, Azure, and Google Cloud) is advantageous.
Successful candidates will also provide mentorship to less experienced members of the team, as well as develop, and lead tutorial sessions on key python or data management topics relevant for group members.
Education:
B.S. in climate / atmosphere / ocean / environmental / computational science or related field
Experience:
Experience with ‘best practices’ of scientific computing and programming and a background in relevant fields, such as climate / atmospheric science / oceanography / meteorology / environmental science or related field is required. Successful candidates are desired to have experience with one or more of the following, data visualization; statistical methods, machine learning and AI-based methods; geospatial data management; familiarity with open science practice; and text to data – or be willing to expand their skill sets accordingly.
For more information and to apply, please see the following:
https://careers-whoi.icims.com/jobs/2298/research-assistant-i-ii/job?hub=8&_gl=1spbd3u_gaMTQ5NTMzMTM2NS4xNzA1NTA4MzQ5_ga_5Y2BYGL910*MTcxMDk1MTM2My44Ni4wLjE3MTA5NTEzNjMuMC4wLjA.&mobile=false&width=1090&height=500&bga=true&needsRedirect=false&jan1offset=-300&jun1offset=-240