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Post Doctoral Fellow - Space Plasmas Data Analytics

Description

Introduction:

The Johns Hopkins University Applied Physics Laboratory is seeking a Postdoctoral Fellow to conduct basic scientific research in the field of Solar and Space Physics with an emphasis on data analytics, machine learning, and uncertainty quantification applied to studies of geospace. The successful candidate will work in an exciting environment, interfacing with experts in state-of-the-art modeling of geospace and other space environment systems, and comprehensive data analysis from a multitude of space missions and ground facilities.

The APL Space Physics Group (SRP) has a broad and active basic research program that includes data analysis, theory and modeling studies of Earth 's magnetosphere and Sun-Earth connections, of other planetary magnetospheres, and of heliospheric and solar physics. It has significant development programs in space instrumentation and mission design. Currently, participation in active missions includes ACE, Geotail, Juno, MMS, New Horizons, Parker Solar Probe, Solar Orbiter, STEREO, and Voyagers 1 and 2. Approved future missions include Europa Clipper, EZIE, JUICE, and IMAP. In addition, the Group is playing the leading role in the multi-institutional cross-disciplinary Center for Geospace Storms, one of the three NASA DRIVE Science Centers recently selected for Phase II. The Group seeks to apply advances in modeling, simulation, and analysis capabilities afforded by increased computational power to augment and maximize the scientific understanding obtained from new and existing space physics data sets, both observational and simulated.

Job Summary:

The research position focusses on applying modern methods of data analytics, machine learning, and uncertainty quantification to a combined analysis of multivariate, heterogeneous, single-point or distributed data sources from a variety of space- and Earth-based assets, including NASA missions and ground facilities, and simulation data from high-resolution global geospace models. The research will include applying these methods to both fundamental studies of the space environment and to validation of the geospace models. The successful candidate would be expected to publish original research in peer-reviewed journals and team with SRP and other APL Space Exploration Sector staff to pursue external support for continued research and development for fundamental simulation research as well as projects relating to past, ongoing, and future missions.

Duties:

1. Conducting original research involving applying modern methods of data analytics, machine learning, and uncertainty quantification to observational and simulation data sets
2. Authoring papers for publication in peer-reviewed journals
3. Preparing for and participating in scientific conferences
4. Developing innovative scientific research efforts and proposing to competed solicitations

Note: This job summary and listing of duties is for the purpose of describing the position and its essential functions at time of hire and may change over time.

Qualifications

Required Qualifications: {C}

The applicant must have completed a PhD in Physics, Math or in a related technical field, or the demonstrated equivalent experience. The applicant must have in-depth knowledge of state-of-the art techniques of data science, machine learning, statistics and uncertainty quantification with applications to scientific research. The applicant must have experience and demonstrated proficiency with advanced technical computing using languages such as Python, Matlab, or another comparable programming language. Prior knowledge of solar or space physics is desirable but not required if extensive experience is demonstrated in applying methods of modern data analytics to scientific research. The applicant must have a record of published first author scientific papers in peer-reviewed journals.

Can demonstrate that you are fully vaccinated against COVID-19. To ensure the safety and well-being of the community, APL has established a policy requiring that all staff be vaccinated against COVID-19. All staff members must provide proof of full vaccination or have an approved medical or religious accommodation by their start date.

Desired Qualifications:

Experience with analysis of observational and simulation data sets in solar and space physics is desirable. Deep knowledge of Python is preferred as is experience with high-performance computing and version control.

Special Working Conditions: Travel to scientific meetings is required.

Why APL:

The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

At APL, we celebrate our differences and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at www.jhuapl.edu/careers

About Us

APL is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to promoting an innovative environment that embraces diversity, encourages creativity, and supports inclusion of new ideas. In doing so, we are committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accommodations@jhuapl.edu. Only by ensuring that everyone’s voice is heard are we empowered to be bold, do great things, and make the world a better place.