The Institute of Mathematics of the Romanian Academy, seeks a scientist with interest in convex optimization with sub-modular functions (or non-sub-modular generalizations), as well as applications in imaging, machine learning, and artificial intelligence: inference in multi-label Markov random fields with high-order dependencies, with emphasis on developing scalable methods in the number of parameters and datasize, as well as Markov decision problems. The ideal candidate would have a relatively recent doctorate degree or equivalent, an excellent publication record, as well as experience and major interests in the area of discrete and/or continuous optimization with large-scale emphasis (programming options in Matlab or C/C++). The candidate must have the interest and the motivation to work full time (or nearly so) within interdisciplinary high-profile teams that would develop mathematical models, theoretical results, algorithms and prototypes in the area of image analysis, or the computational modeling of intelligence (dynamical systems, variational methods and partial differential equations, control). Good communication and team cooperation skills are very much appreciated. The salaries are competitive; the laboratory has excellent computing infrastructure; it is possible to be engaged in high-profile international collaborations and it is also possible to participate in conferences and international scientific venues. Interested applicants with a strong scientific record are invited to send a CV and a statement of research interests, together with the names and academic address of two referees who can be contacted for recommendation letters (do not send letters directly as the institute will require them only if appropriate).
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