Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
-
Field
-
experience in the area of genomics/bioinformatics. You will join a group of academics who are successfully conducting pedagogically-led teaching, lab practicals, workshops, seminars and using forward-thinking
-
or molecular biology, and has relevant skills in bioinformatics. The successful candidate will be committed to the application of their research skills to veterinary clinical questions and especially
-
include several staff and students and we have extensive experience in the development of genomic and bioinformatics tools and methods. We are part of the School of Neuroscience within the Institute
-
of rDNA variation. About You The successful candidate will have a PhD in a relevant subject such as computational biology or bioinformatics, along with significant postdoctoral experience in analysis
-
physics/biophysics/mathematics/bioengineering/bioinformatics/computational science or similar field, including significant experience in programming. In particular, past experience in handling large
-
for this position will have a PhD in physics/biophysics/mathematics/bioengineering /bioinformatics/computational science or similar field, including significant experience in programming. In particular, past
-
in histology, in vivo work, data analysis and acquiring skills such as coding and bioinformatics. About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us
-
bioinformatic and population genomic analytical strategies to sequence data of hosts, vectors, and pathogens across a range of infectious diseases, including malaria. Specific projects will include to understand
-
The Complete University Guide. We hope to fill this position with an academic who has formal training in human/medical genetics and experience in the area of genomics/bioinformatics. You will join a group of
-
, bioinformatics, computer vision and molecular cardiology to explore the mechanisms underlying heart function. The group uses machine learning to analyse cardiac motion for predicting patient outcomes, discovering