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Machine Learning Postdoctoral Scholar

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Postdoctoral Fellow
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CR-Computational Research
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84915 Requisition #
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Berkeley Lab is opening a position for a Postdoctoral Scholar to work in an emerging new area on novel machine learning techniques being applied to computer networking. This work will lead to development of automation and optimization techniques that enable networks to become self-aware and intelligent. The goal of these networks is to effectively support complex distributed science big data needs, across complex multi-domain infrastructure such as DOE facilities. Developments of these techniques will lead to immense impact in next generation scientific discoveries requiring massive amounts of data movement from a variety of sources and emerging new trends with exascale computing.

Leveraging techniques from deep learning, pattern recognition and even artificial intelligence as a whole, this project will explore how large distributed data sets can be processed quickly to predict user behavior and detect anomalies. The postdoc will work as part of unique and engaging team developing techniques linking two major research themes namely network architectures and distributed deep learning methods. This work will lead to impactful results advancing state-of-the-art network research by building networks, that are intelligent and have the ability to understand application-network interaction and programmatically optimize their behavior.

What will you do:

  • Design and develop distributed machine learning approaches that are applicable to networking environment.

  • Develop and use software libraries to process large network data sets that are publicly and privately available.

  • Use data mining and machine learning to better understand relationships between networks and application properties.

  • Research and implement machine learning models that connect fundamental engineering properties of networks to efficient designs.

  • Develop new tools for innovative network solutions that leverage machine learning as part of their design.

  • Apply distributed learning techniques to related fields.

  • Publish research findings in conferences and journals.

Additional Responsibilities as needed:


  • Collaborate with Scientific Networking Division in ESnet at the lab.

  • Collaboration with other teams in DOE facilities and related units.

  • Communicate research results to the wider networking community including industry.

What Is Required:


  • Ph.D. in related field (Computer Science, Any Engineering Discipline (Electronic and Controls, Mathematics).

  • Very strong analytical background in machine learning algorithms, e.g., experience with deep learning analysis and programming libraries.

  • Strong mathematical foundation.

  • Prior ability or demonstrated desire (e.g., papers) in applying machine learning to optimizing engineering problems.

  • Extremely high aptitude and desire for programming and building software infrastructure; object-oriented programming, machine learning libraries. Preferred language of experience is Python but flexible to be extended to Matlab or other machine learning coding experience.

  • Prior ability demonstrated (e.g., Github profile) to contribute to a large software framework.

  • Excellent communication skills that facilitate interdisciplinary work with multiple collaborators.

  • Strong publication history.

  • Demonstrate some history with working with either of the machine learning libraries such as TensorFlow, Keras, Scikit-learn, etc.

Additional desired qualifications:


  • Prior work in the field of network research is a plus.

  • Prior experience in network automation tools is desirable.

  • Prior experience of deploying network architectures and understanding their use is a plus.

  • Any experience with processing streaming large data sets such as over cloud infrastructures and demonstration using software tools is desirable.

The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on September 15, 2018.

Notes:


  • This is a full time, 1-year, postdoctoral appointment with the strong possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. Salary for Postdoctoral positions depends on years of experience post-degree.

  • Full-time, M-F, exempt (monthly paid) from overtime pay.

  • This position is represented by a union for collective bargaining purposes.

  • Salary will be predetermined based on postdoctoral step rates.

  • This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

  • Work will be primarily performed at: Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

Berkeley Lab (LBNL) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.


Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.  Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."


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Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."

 

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The Lawrence Berkeley National Laboratory provides accommodation to otherwise qualified internal and external applicants who are disabled or become disabled and need assistance with the application process. Internal and external applicants that need such assistance may contact the Lawrence Berkeley National Laboratory to request accommodation by telephone at 510-486-7635, by email to eeoaa@lbl.gov or by U.S. mail at EEO/AA Office, One Cyclotron Road, MS90R-2121, Berkeley, CA 94720. These methods of contact have been put in place ONLY to be used by those internal and external applicants requesting accommodation.