ESR 4 position
MSCA ITN founded project “DohART-NET” focusing on effect of altered conditions during the periconceptional (PC) period of development in humans, including babies born from assisted reproduction (ART, “test-tube”) interventions, and from diabetic, obese mothers. The DohART-NET project integrates pre-clinical (animal and stem cell-models) and clinical studies and apply data linkage, bioinformatics and network science for the identification and validation of mechanisms of diseases common in early development. The project will promote efficient disease prevention and potential personalised therapeutic interventions in both the general and ART populations to overcome adverse disease pathways. DohART-NET will train 13 Early Stage Researchers (ESRs) PhD students on this important topic much needed to improve public health over several generations, and it will integrate pre-clinical, translational clinical and in silico modeling approaches. The ESRs will strongly benefit from a network of internationally recognized scientists and the participation of companies with relevant interests and expertise in the field.
DohART-NET Network: BioTalentum Ltd. (Hungary), University of Cambridge (UK), University of Manchester (UK), University of Southampton (UK), Erasmus University Medical Center (Netherlands), CeMM (Austria), Ludwig Maximilian University of Munich (Germany), MWM GmbH (Germany), Universitair Ziekenhuis Brussel (Belgium), IVI Valencia (Spain)
Job Title: PhD Position (ESR4)
Application Deadline: 14th July 2019
Recruiting Institution: University of Manchester, UK
The applicant will develop a multidisciplinary project focused on the growth and long term health of children conceived by Assisted Reproduction Treatment (ART). The project will utilize databases of ART held by the UK Human Fertilisation and Embryology Authority and child growth and health outcomes held by the National Health Service, using established linkages and also developing novel methodology. In a previous study we have shown that ART children tend to have low birthweight and altered postnatal growth, both associated with long term disease risk in adults. The aim of the project is therefore to quantify any effects of ART on long-term offspring health, and identify the underlying causal pathways and factors which might be modified to make ART safer.
The candidate should have solid knowledge of statistical and epidemiological methodology and data processing, ideally with a Masters level qualification in epidemiology or statistics. Practical experience in handling large databases and in statistical analysis would be preferred, but not required.
Regular meetings and workshops within the EU-funded DohART-NET International Training Network will supplement the training and support provided at University of Manchester. The successful candidate will also benefit from work secondments in the participating academic and industrial teams.
The appointment will be on a temporary basis for a period of 36 months (Regular employment contract). The candidate will receive a Monthly Living Allowance plus a Mobility Allowance compliant with the applicable EC Marie Skłodowska-Curie Actions-ITN general conditions.
Applicants should meet the following eligibility criteria:
- have a good knowledge of applied Statistics and epidemiology.
- have not been awarded a PhD already
- have less than 4 years of full time – including any period of research experience at the signature of the contract
(This is measured from the date when the degree was obtained, which formally entitles the candidate to embark a doctorate, either in the country in which the degree was obtained, or in the country in which the research training is provided. Degree: MSc, MD, DVM and BSC in some countries.)
- at the time of selection, the candidate must have not resided or carried out their main activity (work, studies, etc.) in the country of their host organization/recruiting institution for more than 12 months in the 3 years immediately prior to selection. Short stays such as holidays are not considered.
- excellent knowledge of the spoken and written English language
- excellent communication and team working skills
How to Apply and further details:
Follow the below steps to submit your application. Please note all the uploaded documents should be written in English and should be in PDF format.
1. Please answer the questions below
2. Fill in the required fields
3. Upload your CV
4. Upload your motivation letter describing research career goals, skills and experience
5. Upload 2 letters of recommendation