Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against
-
that include applicants from all backgrounds and communities. We ask all candidates to submit a copy of their CV, and a supporting statement detailing how they meet the essential criteria listed in the advert
-
(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
-
] Subject Areas: Random matrices, quantum chaos, mathematical physics, applied probability Appl Deadline: none (listed until 2025/05/30) Position Description: Position Description Postdoctoral Position in
-
, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine learning) or a directly related field at the time of appointment is required. The successful applicant
-
flow control, in collaboration with researchers at the Arizona State University. The position would suit a theoretician with a strong control engineering or mathematical background. The successful
-
. Qualification requirements The selected candidate should have a master’s degree in a related field: e.g., civil engineering , mechanical engineering , computational materials science , or applied mathematics
-
-certification, and redeployment, as well as social acceptability and policy design. About you You should hold a relevant PhD/DPhil, or be near completion, in electrical engineering, economics, applied mathematics
-
contributes meaningfully to the broader scientific field. Your competencies The successful candidates should have excellent grades, strong mathematical and simulation skills and problem-solving mind-sets. It is
-
participants, and mathematical / statistical modeling. Requirements for employment are a completed PhD degree in a relevant field (Linguistics, Cognitive Science, Psychology, Philosophy, or similar), near native