ESR 11 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 (ESR11)
Application Deadline: 14th July 2019
Recruiting Institution: MWM GmbH – Munich, DE
The applicant will develop a multidisciplinary project focused on assessing the health outcomes in neonatal offspring from genetically (pre-)diabetic sows as compared to neonatal offspring from wild-type littermate sows; to evaluate changes in glucose metabolism in vivo and to establish a comprehensive repository of about 50 different body fluids/tissues for systematic clinical-chemical, endocrinological, metabolomics as well as molecular profiling on the RNA and protein levels.
The ideal candidate should have solid knowledge in endocrinology and pathology. Practical experience in molecular profiling techniques, together with bioinformatics competences, is strongly preferred but not required.
The project implies a series of secondments at partner labs for additional training. The successful candidate will participate in the network’s training activities and work placements at the laboratories of the participating academic and industrial teams. Regular meetings and workshops within the EU-funded DohART-NET International Training Network will supplement the training and support provided at MWM Biomodels GmbH and LMU Munich.
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 background in veterinary medicine, biology or biochemistry
- 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.)
- have not spent more than 12 months in the country of the host/recruiting institution in the 3 years prior to selection
- 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