Lawrence Livermore National Laboratory



ChemBio Data Scientist

Location:  Livermore, CA
Category:  Science & Engineering
Organization:  Computation
Posting Requirement:  External w/ US Citizenship
Job ID: 103786
Job Code: Science & Engineering MTS 2 (SES.2) / Science & Engineering MTS 3 (SES.3)
Date Posted: May 15 2018

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Science and Technology on a Mission!

For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place.

We have an opening for a Chemical/Biological Data Scientist.  You will perform work in a challenging R&D environment in support of the Laboratory's programs using pharmacology, molecular dynamics simulations, experimental data modeling and computer science in the area of drug design. This position will be located at LLNL’s Mission Bay site in San Francisco. This position is within the Global Security Computing Applications Division GS-CAD of the Computation Directorate.

This position will be filled at either the SES.2 or SES.3 level depending on your qualifications. Additional job responsibilities (outlined below) will be assigned if you are selected at the higher level.

Essential Duties
- Collaborate with scientists and researchers in one or more of the following areas: machine learning, statistical learning, information visualization, data integration, scientific data mining, database technology, scalable tool development, and High Performance Computing (HPC)simulation and evaluation.
- Work with other LLNL scientists and application developers to develop machine learning models for predicting properties of chemical compounds.
- Carry out development of moderately complex data analysis algorithms to address program and sponsor data sciences requirements.
- Engage other developers frequently to share relevant knowledge, opinions, and recommendations, working to fulfill deliverables as a team.
- Design technical solutions with limited direction, participate as a member of a multidisciplinary team to design, and implement software and perform analyses to address project requirements.
- Perform other duties as assigned.
In Addition at the SES.3 Level
- Lead design and development of a data science project to ensure complex tasks and deadlines are met.
- Utilize team members skills to complete complex projects/tasks, and solve abstract complex problems/ideas and convert them into useable algorithms/software modules.
- Provide solutions that require in-depth analysis of multiple factors and the creative use of established methods.

Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, Computational Biology, Computational Chemistry, or related field, or the equivalent combination of education and related experience.
- Comprehensive knowledge of one or more of the following: scientific data analysis, statistical analysis, deep learning, unsupervised learning, active learning, data management technologies.
- Experience in pharmacology or toxicology and molecular simulations or statistical modeling of experimental data in molecular biology.
- Broad experience developing software with C++, C, Java, Python, R, or Matlab in Linux or Windows, data analysis algorithms, data management approaches, relational databases, or machine learning algorithms.
- Experience with one or more deep learning libraries such as TensorFlow, Torch, Caffe, Keras, or Theano.
- Effective interpersonal skills necessary to interact with all levels of personnel.
- Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.
In Addition at the SES.3 Level
- Advanced analytical, problem-solving, and decision-making skills to develop creative solutions to complex problems, as well as advanced verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management.
- Significant experience with developing and training deep learning models on chemical or molecular biology data, as well as experience developing one or more of the following: machine learning models trained on molecular simulation data, active learning to guide model development, and uncertainty quantification on deep learning models.

Desired Qualifications
- Master’s degree or Ph.D. in computer science, computer engineering, computational biology, computational chemistry, or related field.- Publication record demonstrating research in the area of machine learning and/or computational biology or computational chemistry.

Pre-Employment Drug Test:  External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test.
 

Security Clearance:  This position requires a Department of Energy (DOE) Q-level clearance.

If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship.  If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted.

Note:   This is a Career Indefinite position. Lab employees and external candidates may be considered for this position.

About Us

Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE). LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance. The Laboratory has a current annual budget of about $1.8 billion, employing approximately 6,500 employees.

LLNL is an affirmative action/ equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, protected veteran status, age, citizenship, or any other characteristic protected by law.

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