AI/ML Job: Sr. Machine Learning Researcher

The Johns Hopkins Applied Physics Laboratory

Sr. Machine Learning Researcher at The Johns Hopkins Applied Physics Laboratory

Laurel, Maryland, United States 🇺🇸   (Posted Sep 12 2018)
About the company
The Johns Hopkins Applied Physics Laboratory (APL) is a not-for-profit, university-affiliated research center (UARC) that solves complex research, engineering, and analytical problems that present critical challenges to our nation. Located north of Washington, DC, APL is a division of one of the world's leading research institutions, The Johns Hopkins University.

Job position
Permanent

Job description
The Johns Hopkins Applied Physics Laboratory (APL) is a national leader in scientific research and development. APL is actively seeking a Sr. Machine Learning Researcher, for the Intelligent Systems Group. The Johns Hopkins Applied Physics Laboratory (APL) is located midway between Baltimore and Washington, DC.

Introduction:

The Intelligent Systems Group (ISG), of the Research & Exploratory Development Department (REDD), at the Johns Hopkins University Applied Physics Laboratory (JHU/APL), is a multidisciplinary team of scientists and engineers focused on developing the next generation of intelligent systems for the U.S. Government. Disciplines within the ISG include machine learning, autonomy, applied neuroscience, robotics, data science, and semantics.

Job Summary:

The highly motivated researcher will contribute and\or lead advanced R&D projects in the broad area of machine intelligence including machine perception, adversarial machine learning, deep reinforcement learning, and reasoning under uncertainty.

Duties (Listed in order of importance with the estimated amount of time spent at each task):

1.Develop, apply, and implement machine learning methods (such as deep learning, reinforcement learning, neurally inspired AI) to enable real-world applications in robotics and autonomy, data science, neuroscience, and health and medicine.

2.Conduct original algorithmic research in novel machine learning architecture and computational methods to overcome key technical barriers for the development of artificial general intelligence capabilities in the areas of data paucity, uncertainty, domain adaptation, and adversarial perturbations.

3.Provide input to team leads and other researchers to help define research vision and inform technical direction, and support reporting of accomplishments and contributions to sponsors and research community.

4.Write scientific manuscripts and whitepapers summarizing results to communicate impact of research, develop concepts of operation with mission relevance, and engage with sponsor and stakeholder community.

Note: This job summary and listing of duties is for the purpose of describing the position and its essential functions at time of hire and may change over time.

Skills & requirements
Required Qualifications:

•Ph.D. in Mathematics, Computer Science, Computer Engineering, Optimization, or related field and 5+ years of experience.

•Demonstrated ability in selecting, developing, and applying machine learning and data mining algorithms.

•Experience dealing with large data sets.

•Fluent, with hands-on experience in at least one of the standard development tools/languages such as Python, Java, C++/C, MATLAB, and R.

•Excellent written and oral communication skills; ability to articulate complex technical issues effectively and appropriately for a wide range of audiences.

Desired Qualifications:

•Demonstrated capability to carry out original machine learning research beyond incremental application of existing techniques, as evidenced by publications in premier conferences.

•Research records that illustrate in-depth understanding of underlying theory necessary to develop novel algorithms to address unique real-world challenges.

•Extensive experience in developing and applying machine learning algorithms in application settings such as robotics, autonomous systems, neuroscience, and healthcare.

•Research experience with advanced machine learning research topics such as deep reinforcement learning, unsupervised and semi-supervised learning, imagination-augmented planning, integration of deep learning and knowledge-based reasoning, and adversarial machine learning.

Security: Applicant selected will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

Instructions how to apply
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