450 proof-checking-postdoc-computer-science-logic positions at University of Cambridge
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
Library, to receive new library material to the LSF, perform bibliographical checking, sort and enter it on to the online Warehouse Management System (WMS). Using a variety of manual handling vehicles
-
achieved through the Isaac Science free online platform and through a weekly programme of work and tutorials in our STEM SMART programme (https://www.undergraduate.study.cam.ac.uk/stem-smart ) which will
-
development of all members. We share open-plan lab space with two zebrafish groups. We are looking for a second postdoc to join the lab for a Leverhulme Trust-funded project on the development and evolution
-
neuroscience, with the aim of improving mental health outcomes in both non-clinical and clinical populations. We are based at the MRC Cognition and Brain Sciences Unit, University of Cambridge, a world-leading
-
The Office of the School of the Physical Sciences is seeking an exceptional and highly organised Industry Engagement Administrator to provide dedicated support to the Industry Training Development
-
of an integrated approach to risk-stratified screening, following the success of the BRAID trial. This work will help inform NHS Breast Screening Programme policy, assessing the value of supplemental imaging based
-
through the Isaac Science free online platform and through a weekly programme of work and tutorials in our STEM SMART programme (https://www.undergraduate.study.cam.ac.uk/stem-smart ) which will develop a
-
. Applications are invited for this one-year post-graduate training programme based in the Queen's Veterinary School Small Animal Hospital. On site accommodation is available for £300 per month including bills
-
. The appointee will have a minimum Bachelor's degree in biological science, ideally in science related field, or appropriate experience or equivalent qualification and/or experience. Knowledge of the day-to-day
-
will be addressed using a series of behavioural and electro-physiological experiments with Cochlear Implant users, as well as comparing the outcomes with predictions from existing computational models