15 communication-wireless-security Postdoctoral positions at Brookhaven National Laboratory
Sort by
Refine Your Search
-
. Solid background in electron microscopy and structural characterization. Ability to communicate and work effectively within a diverse multi-disciplinary and multi-institutional team environment. Ability
-
develop novel and improved platforms for quantum computation and communication and thus strengthen U.S. leadership in QIST. This calls for expertise across disciplinary sciences – encompassing quantum
-
. The mission is to address challenges facing scalable quantum computing and to develop novel and improved platforms for quantum computation and communication and thus strengthen U.S. leadership in QIST
-
discipline is required within the last 5 years. Candidates must have excellent written and oral communication skills, be self-motivated and able to work independently. Trained as a theorist in either condensed
-
availability of funding. Required Knowledge, Skills, and Abilities: *Ph.D. in Physics or related discipline is required within the last 5 years. *Candidates must have excellent written and oral communication
-
a particular focus on grid applications of large language models (LLMs) and foundation models (FMs) to ensure the energy security and operational reliability of electric power systems. Required
-
. This position has a high level of interaction with an international and multicultural scientific community. Essential Duties and Responsibilities: Designing and conducting experiments. Establishing and
-
information at BNL | Benefits Program The Environment, Biology, Nuclear Science & Nonproliferation Directorate conducts fundamental research and develops technology to enable the transition to a secure
-
and/or Matlab programming. * Good written and oral communication skills, be willing to take direction, and be able to work with others as part of a project team. Preferred Knowledge, Skills, and
-
working on diverse scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) development of novel machine learning models and