[DMANET] Machine Learning and Graph Theory Postdoc

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Postdoctoral Position
Los Alamos National Laboratory
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The Information Sciences group and the Center for Nonlinear Studies at the Los Alamos National Laboratory have an opening at a postdoctoral level. The research will involve elements of machine learning and graph theory. It will be a part of a multi-disciplinary project in high-performance simulation that is based on a dynamic graph modeling of physical processes.

Candidates are expected to have strong analytical and programming skills. The successful applicant should have a strong publication record and will be expected to publish results in high impact peer-reviewed journals and conferences. This is a long-term appointment (up to three years), so candidates who can commit to a longer time frame will be preferred. However, candidates available for shorter periods may be considered for internships.

Qualifications:

(1) A PhD in Computer Science, Computer Engineering, or Mathematics;
(2) Research-level expertise in at least one of the following: machine learning, graph theory;
(3) Strong programming skills;
(4) Demonstrated ability to publish research in peer-reviewed journals or conference proceedings in the areas of machine learning and/or graph theory;
(5) Excellent oral presentation and writing skills
(6) Willingness to work in interdisciplinary project teams and learn about other fields

Applications received before October 31, 2016 will receive a full consideration.

US citizenship is NOT required for this position.

For full details and instructions on how to apply go to https://jobszp1.lanl.gov:443/OA_HTML/OA.jsp?OAFunc=IRC_VIS_VAC_DISPLAY&OAMC=R&p_svid=51658&p_spid=2355270&p_lang_code=US<https://jobszp1.lanl.gov/OA_HTML/OA.jsp?OAFunc=IRC_VIS_VAC_DISPLAY&OAMC=R&p_svid=51658&p_spid=2355270&p_lang_code=US>. For informal inquiries you can contact Hristo Djidjev, djidjev@lanl.gov<mailto:djidjev@lanl.gov>.


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