Job Information
Pacific Northwest National Laboratory William R. Wiley Postdoctoral Fellow in Austin, Texas
Overview
The Earth and Biological Sciences Directorate (EBSD) at Pacific Northwest National Laboratory (PNNL) is at the forefront of pioneering research in Atmospheric and Climate Sciences, Biological Sciences, and Environmental Molecular Sciences. Our staff's contributions are integral to advancing PNNL's mission of understanding, predicting, and controlling the complex adaptive systems that underpin Earth, energy, and security science. Within EBSD, the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) is a premier national scientific user facility – supported by the U.S. Department of Energy's Office of Biological and Environmental Research (BER) – offering cutting-edge experimental and computational resources, with over 75 state-of-the-art instruments and capabilities. EMSL Users tackle critical molecular-to-mesoscale challenges aligned with DOE's objectives, driving innovative and transformative science. Join us in shaping the future of scientific discovery and impact at PNNL.
Responsibilities
The Environmental Molecular Sciences Division is seeking applications for the William R. Wiley Postdoctoral Fellowship. This year’s Wiley Fellowship is focused on data science with expertise in artificial intelligence and machine learning (AI/ML). The ideal candidate will have a strong foundational background in applied mathematics, data science, or AI/ML, and demonstrated experience applying their skills to unravel stories contained in multimodal chemical imaging data towards understanding biogeochemical, microbial and environmental processes. The Wiley Fellow will be embedded in the EMSL User Facility and perform collaborative research with external researchers and with PNNL and EMSL scientists. Research activities will include development and deployment of analysis pipelines, new algorithmic approaches, and machine learning methods enabling analysis of multimodal chemical imaging data, with an end goal of improving our ability to understand fundamental mechanisms governing the stabilization of organic carbon in soils. This position will provide opportunities to work and collaborate with a diverse team of soil and geochemists, microbiologists, rhizosphere scientists, and other domain experts to translate research objectives into data-driven solutions.
These research efforts will provide the successful candidate with opportunities to integrate state-of-the-art observational data taken at EMSL (including X-ray tomography, electron microscopy, spectral imaging, mass spectrometry, and genomic information) into a unified source of information for modeling complex systems. Familiarity with modern data science and machine learning tools such as PyTorch or equivalent is required, preferably within an imaging setting. The candidate should possess excellent oral and written communication skills and strong interpersonal skills. The applicant will be expected to contribute to ideas and methods expanding on existing R&D, to collaborate on reports, proposals, papers, posters, and presentations, and to develop external collaborations with users and other scientists. The candidate must also demonstrate initiative, creativity, and innovative thinking, and high tolerance for the ambiguity, dynamics, and diversity of work that are characteristic of a research environment.
Candidates are encouraged to provide a cover letter as an attachment to this application under “Additional Documents.” In the cover letter, please describe your research interests as well as how these research activities would advance your career development and goals. The ideal candidate will relocate to the Richland, WA campus, but exceptional candidates may be considered for a remote arrangement.
Qualifications
Minimum Qualifications:
- Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.
Preferred Qualifications:
PhD with image data-related research experience.
PhD in Chemistry, Biochemistry, Biology, Mineralogy, Environmental Engineering, Applied Mathematics, Machine learning, Data Science or a related field.
Documented experience with Python and associated tools in data science and AI/ML, such as PyTorch, JAX, or TensorFlow.
Ability to adapt, refine, or innovate experimental or computational tools based on project needs.
Proven ability to plan and execute research tasks and take initiative in the completion of tasks important to the projects. These include preparation of first drafts of papers for peer-reviewed journals, and technical presentations at scientific conferences.
Ability to work in collaboration with a multi-disciplinary group of scientists and technical staff, ability to communicate effectively with experimentalist and computational modeling colleagues.
Strong verbal and written communications skills.
Experience in chemical imaging and related software tools, soil mineralogy, chemistry, microbiology or soil physics, x-ray spectroscopies, x-ray diffraction/scattering, x-ray computed tomography, energy dispersive spectroscopy, hyperspectral imaging, mass spectroscopy imaging.
Experience with any of these software tools is a plus: ImageJ/Fiji, Avizo, VG Studio, Dragonfly, Aztec.
Hazardous Working Conditions/Environment
Not applicable
Additional Information
Not applicable
About PNNL
Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!
At PNNL, you will find an exciting research environment and excellent benefits including health insurance, flexible work schedules and telework options. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or 3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.
Commitment to Excellence, Diversity, Equity, Inclusion, and Equal Employment Opportunity
Our laboratory is committed to a diverse and inclusive work environment dedicated to solving critical challenges in fundamental sciences, national security, and energy resiliency. We are proud to be an Equal Employment Opportunity and Affirmative Action employer. In support of this commitment, we encourage people of all racial/ethnic identities, women, veterans, and individuals with disabilities to apply for employment.
Pacific Northwest National Laboratory considers all applicants for employment without regard to race, religion, color, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.
We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov .
Drug Free Workplace
PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.
If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.
HSPD-12 PIV Credential Requirement
In accordance with Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, new employees are required to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
Mandatory Requirements
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
Rockstar Rewards
Employees and their families are offered medical insurance, dental insurance, vision insurance, health savings account, flexible spending accounts, basic life insurance, disability insurance, employee assistance program, business travel insurance, tuition assistance, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company funded pension plan and may enroll in our 401k savings plan. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.
- Research Associates excluded.
**Once eligibility requirements are met.
Click Here For Rockstar Rewards (https://careers.pnnl.gov/rockstar-rewards)
Notice to Applicants
PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual’s relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.
As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.
Minimum Salary
USD $69,000.00/Yr.
Maximum Salary
USD $119,100.00/Yr.