Job ID: 102176
Job date: 2017-08-05
End Date:
Company : Lawrence Livermore National Laboratory Country : Role : Other
Job date: 2017-08-05
End Date:
Company : Lawrence Livermore National Laboratory Country : Role : Other
Job Description:
We have multiple openings for Engineers, Computer Scientists, Data Engineers, Applied Statisticians, or Applied Mathematicians. You will conduct basic and applied research in Machine Learning for automated understanding of massive multimodal data. At LLNL we are developing new Machine Learning technologies, enabled by our world-class supercomputing facilities, to train and analyze the largest datasets in support of our national security and national science applications. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate. These positions 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: - Integrate algorithms within larger programmatic systems that require these capabilities. - Perform experimental analysis efforts using state-of-the-art Machine Learning algorithms. - Conduct research in Machine Learning to enable development of new state-of-the-art algorithms for Laboratory problem domains. - Interact with inter-organizational contacts and/or external customers. - Provide input on technical issues for specific projects including preparing and presenting technical reports. - Perform other duties as assigned. In Addition at the SES.3 Level: - Develop and implement Machine Learning algorithms for classification, clustering, prediction, or anomaly detection applications. - Guide the completion of projects and contribute to the development of organizational objectives and fully function as a team member on multidisciplinary teams. - Interact with professional colleagues, mid-level internal management, and sponsor representatives on matters requiring coordination across organizational lines. Represent the organization as the primary technical contact on tasks and projects. Serve on internal technical/advisory committees and may serve on external committees. Qualifications: - Master’s degree in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology, or a related field or the equivalent combination of education and related experience. - Experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, unsupervised feature learning, reinforcement learning, zero- or few-shot learning, multimodal learning, natural language processing, ensemble methods, scalable density estimation, scalable online inference, and probabilistic graphical models. - Comprehensive knowledge and experience in Machine Learning including experience in algorithm development. - Experience in the broad application of one or more higher-level programming languages such as C/C++, Java/Scala, or Python. - Experience with one or more scientific analysis and prototyping environments such as R, MATLAB, or the SciPy Stack. - Demonstrated 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: - Significant advanced application and development in one or more higher-level programming languages such as C/C++, Java/Scala, or Python. - Significant experience with one or more scientific analysis and prototyping environments such as R, MATLAB, or the SciPy Stack. - 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. Desired Qualifications: - PhD in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology, or a related field. - Demonstrated proficiency in developing and writing technical proposals and have an established publication record. - Experience and expertise with Deep Learning models and libraries and GPU programming and parallel algorithm development.
Additional Info:
For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place. 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 either no security clearance, or a Department of Energy (DOE) L-level or Q-level clearance depending on the location of the assignment. If you are selected and a security clearance is required, 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. 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: Text revised effective July 12, 2017. Relisted position. Originally listed on March 29, 2017. Previous candidates need not reapply. This listing has multiple openings; these are Career Indefinite positions. Lab employees and external candidates may be considered for these positions. 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 $1.5 billion, employing approximately 6,000 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.[Click Here to Access the Original Job Post]
We have multiple openings for Engineers, Computer Scientists, Data Engineers, Applied Statisticians, or Applied Mathematicians. You will conduct basic and applied research in Machine Learning for automated understanding of massive multimodal data. At LLNL we are developing new Machine Learning technologies, enabled by our world-class supercomputing facilities, to train and analyze the largest datasets in support of our national security and national science applications. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate. These positions 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: - Integrate algorithms within larger programmatic systems that require these capabilities. - Perform experimental analysis efforts using state-of-the-art Machine Learning algorithms. - Conduct research in Machine Learning to enable development of new state-of-the-art algorithms for Laboratory problem domains. - Interact with inter-organizational contacts and/or external customers. - Provide input on technical issues for specific projects including preparing and presenting technical reports. - Perform other duties as assigned. In Addition at the SES.3 Level: - Develop and implement Machine Learning algorithms for classification, clustering, prediction, or anomaly detection applications. - Guide the completion of projects and contribute to the development of organizational objectives and fully function as a team member on multidisciplinary teams. - Interact with professional colleagues, mid-level internal management, and sponsor representatives on matters requiring coordination across organizational lines. Represent the organization as the primary technical contact on tasks and projects. Serve on internal technical/advisory committees and may serve on external committees. Qualifications: - Master’s degree in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology, or a related field or the equivalent combination of education and related experience. - Experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, unsupervised feature learning, reinforcement learning, zero- or few-shot learning, multimodal learning, natural language processing, ensemble methods, scalable density estimation, scalable online inference, and probabilistic graphical models. - Comprehensive knowledge and experience in Machine Learning including experience in algorithm development. - Experience in the broad application of one or more higher-level programming languages such as C/C++, Java/Scala, or Python. - Experience with one or more scientific analysis and prototyping environments such as R, MATLAB, or the SciPy Stack. - Demonstrated 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: - Significant advanced application and development in one or more higher-level programming languages such as C/C++, Java/Scala, or Python. - Significant experience with one or more scientific analysis and prototyping environments such as R, MATLAB, or the SciPy Stack. - 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. Desired Qualifications: - PhD in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology, or a related field. - Demonstrated proficiency in developing and writing technical proposals and have an established publication record. - Experience and expertise with Deep Learning models and libraries and GPU programming and parallel algorithm development.
Requeriments :
- M.Sc. or higher Degree in computational biology
- M.Sc. or higher Degree in Computer Science
- M.Sc. or higher Degree in Statistics
- Master's Degree in Engineering
Skills :
- Machine Learning
- Parallel Computing
- Programing in C
- Programing in C++
- Programing in Python
- Programing Skills
- Programming in Java
- Programming in Matlab
- Programming in R
Areas :
Additional Info:
For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place. 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 either no security clearance, or a Department of Energy (DOE) L-level or Q-level clearance depending on the location of the assignment. If you are selected and a security clearance is required, 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. 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: Text revised effective July 12, 2017. Relisted position. Originally listed on March 29, 2017. Previous candidates need not reapply. This listing has multiple openings; these are Career Indefinite positions. Lab employees and external candidates may be considered for these positions. 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 $1.5 billion, employing approximately 6,000 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.[Click Here to Access the Original Job Post]