117 proof-checking-postdoc-computer-science-logic Fellowship positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
into the RTG ACME's comprehensive and interdisciplinary training program with structured joint training of doctoral students in natural sciences and medicine and early-career medical and clinician scientists
-
, Cell Biology, Biochemistry Physics, (Electrical) Engineering, Statistics, Computer Science or a related field. Description: This is a full-time postdoctoral fellow position in a neurobiology laboratory
-
, quantitative field, e.g. atmospheric or climate science, meteorology, computer science, data-science, physics, mathematics, statistics, environmental science or related fields Evidence of a good understanding
-
Program . Job description The fellowships are aimed at early-career researchers with a basic science background or clinicians who aspire to a career in academia. We are particularly interested in candidates
-
Position Details School of Chemical Engineering Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,130 to £45,413 with potential
-
and values diversity acting as a role model and fostering an inclusive working culture Person Specification Essential: PhD (or near completion) in Computer Science, Data Science, AI, or a related field
-
The University of Toronto is pleased to announce the third call for applications for theEric and Wendy Schmidt AI in Science Postdoctoral Fellowship , a program of Schmidt Sciences, which brings
-
to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research project. Our international group of highly motivated and
-
The SQUASH Program is a prestigious Marie Skłodowska-Curie COFUND initiative offering 3-year postdoctoral positions in quantum science and technology. This 1st international call invites outstanding
-
methodologies, and publish at a high level. The lab offers deep integration between wet-lab and computational biology, and close connections to institutional resources and collaborative networks across Duke-NUS