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MRC DTP PDN Projects 2017

The following PDN projects are available for October 2017

Visit the Cambridge MRC DTP website for information on how to apply.

 

Population and Systems Medicine Projects

Placental endocrine function and materno-fetal resource allocation during pregnancy
Supervisor: Dr. Amanda Sferruzzi-Perri     Project ID: PSM16

Cardiac arrhythmia risk screening using ECG complexity analysis
Supervisor: Dr. James Fraser     Project ID: PSM8

Atrial fibrillation associated with genetic modification of a Na+ channel ancillary beta-3 subunit.
Supervisor: Prof. Christopher Huang     Project ID: PSM4


Infections & Immunity Projects

Elucidating how chemokines guide neutrophil migration to sites of infection
Supervisor:Dr. Milka Sarris     Project ID: II13



Molecular and Cellular Projects

Embryonic fate, stem-ness, and metabolic determination
Supervisor: Prof. Randall Johnson     Project ID: MC31

Programming the Notch response
Supervisor: Prof. Sarah Bray     Project ID: MC43

Molecular mechanisms underlying olfactory ensheathing cell (OEC) development from the neural crest
Supervisor: Dr. Clare Baker     Project ID: MC7


Neurosciences and Mental Health Projects

AMPA receptor subunits and the expression of LTP
Supervisor: Prof. Ole Paulsen     Project ID: NMH31

Neural basis of emotion regulation
Supervisor: Prof. Angela Roberts     Project ID: NMH13

Impact of maternal obesity on the long-term mental health of offspring
Supervisor: Prof. Abigail Fowden     Project ID: NMH39

RSS Feed Latest news

Magdalena Zernicka-Goetz awarded international IVI Foundation Award

Apr 21, 2017

Prof Zernicka-Goetz was awarded the IVI Foundation Award for Basic Research in Reproductive Medicine 2017.

Algorithm matches genetic variation to disease symptoms and could improve diagnosis of rare diseases

Apr 21, 2017

A faster and more accurate method of identifying which of an individual’s genes are associated with particular symptoms has been developed by a team of researchers from the UK and Saudi Arabia. This new approach could enable scientists to take advantage of recent developments in genome sequencing to improve diagnosis and potential treatment options.

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