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Data Science in Environment and Wildland Fire Postdoc

Company: Los Alamos National Laboratory
Location: Los Alamos
Posted on: November 22, 2022

Job Description:

**What You Will Do**

We seek a motivated candidate for a postdoctoral research position in data science, machine learning, computer vision, and/or statistics with experience and interest in remote sensing and point cloud processing for environmental applications. You will be working on a highly-interdisciplinary multi-faceted Earth science project, analyzing data, including LiDAR-derived point clouds and other in-situ and remotely sensed datasets. This work will require research and development of methods and tools to characterize the environment relevant to wildland fire, particularly prescribed fire. These analyses will be used to improve the capability of high-performance simulations of wildland fire behavior, and their use to land managers. This project has real impact to the critical situation of mitigating wildfire hazards.

This project offers great potential for you to publish, both methodological papers within the machine learning community as well as applied papers in the Earth sciences domain. Furthermore, you will have the opportunity to develop software crucial to the national security mission, and gain experience in the use of high-performance computing (HPC) tools for fast implementation.

**What You Need**

**Minimum Job Requirements:**

**Education/Experience** :

This position requires:

--- PhD in Machine Learning, Computer Science, Applied Math and Statistics, or related field completed within the past five years, or will have completed all PhD requirements by commencement of appointment.

--- Experience and interest in Earth and environmental science data analysis applications.

--- Willingness to work with field-collected datasets as well as physics simulation codes.

--- Demonstrated ability to engage productively with a collaborative, interdisciplinary team.

**Desired Qualifications:**

Candidates will benefit from experience in any of:

+ pointcloud data processing and analysis

+ spatial/environmental applications

+ uncertainty quantification

+ graph/network models

+ strong working knowledge of python

+ knowledge and experience in platforms for machine learning, for example tensorflow and/or pyTorch

+ C/C++ or Fortran programming in HPC environments

+ GPU computing

**Location:** This position will be located in Los Alamos, NM.

**COVID Vaccine:**

The COVID vaccine is mandatory for all employees, on-site contractors, and on-site subcontractors unless granted an accommodation under applicable state or federal law. This requirement will apply to those working on-site, those teleworking, and all new hires.

**Note to Applicants:**

In addition to applying online, please send a CV, contact information for three references, one-page statement of research interests, and a cover letter summarizing research and career goals.

**Where You Will Work**

Our workforce enjoys a collegial work environment focused on creative problem solving. We are committed to work-life balance, as well as both personal and professional growth. Los Alamos, New Mexico, enjoys excellent weather, clean air, outstanding public schools and quick, easy access to many top ski resorts, scenic hiking and biking trails, and to a range of recreational pursuits. Many employees enjoy the proximity to the nearby state capital, Santa Fe, which is known for world-class restaurants, art galleries, opera, and cultural events.

Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:

- PPO or High Deductible medical insurance with the same large nationwide network

- Dental and vision insurance

- Free basic life and disability insurance

- Paid childbirth and parental leave

- Award-winning 401(k) (6% matching plus 3.5% annually)

- Learning opportunities and tuition assistance

- Flexible schedules and time off (paid sick, vacation, and holidays)

- Onsite gyms and wellness programs

- Extensive relocation packages (outside a 50 mile radius)

**Additional Details**

**Directive 206.2** - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.

Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks.

**New-Employment Drug Test:** The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.

**Equal Opportunity:** Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation or preference, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to applyhelp@lanl.gov or call 1-505-665-4444 option 1.Employment StatusFull Time

Keywords: Los Alamos National Laboratory, Santa Fe , Data Science in Environment and Wildland Fire Postdoc, Other , Los Alamos, New Mexico

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