Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
, Computer Science, Electrical/ Telecommunications Engineering, Mathematics, or related field. Ability to conduct research in an academic or commercial environment. Expertise in optimization techniques, graph theory
-
-doctoral associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be
-
work, studying in disciplines ranging from atomic physics and graph theory to medieval literature and blind rehabilitation. Of 101 graduate offerings available, 30 lead to a doctoral degree. Connections
-
architecture and design for complex socio-technical systems Graph theory, network science, and knowledge representation Agent-based and simulation modeling AI/ML, foundation models, causal inference, and
-
of distributed frameworks and systems, to experimental evaluation and verification. The Ph.D. student will work in an interdisciplinary environment at the intersection of distributed systems, graph theory, and
-
to students pursuing degrees through the doctoral level. More than 20 percent of its 25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory
-
positions for distinguished professorship. Candidates in areas including, but not limited to, Algebra, Number Theory, Geometry, Topology, Combinatorics, Graph Theory are encouraged to apply. Responsibilities
-
theory, principles, and practices of management techniques to make effective judgments and recommendations. Demonstrated skills to communicate efficiently and effectively (both orally and written) with all
-
discipline; A candidate with experience in computer programming and data management will be given preference; Experience with graph theory and graphic libraries such as Gephi or NetworkX.; Experience with
-
and Sobolev-type spaces (with Hytönen and/or Korte), Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game