The Department of Biostatistics at UMCU/Julius center is recruiting an Early Stage Researcher (ESR) to IMforFUTURE (Innovative training in Methods for FUTURE data) project, a new, EU funded Marie-Curie Initial Training Network, starting in 2017. This is a generously funded position with a focus on training and transfer of skills, and will therefore involve secondments at a collaborating institution of between two and six months. The ESR position will involve registration for a PhD, and will last for 36 months.
As the successful candidate for this PhD position, you will develop Statistical methods for integrative analysis for omics data, namely latent variable models for integration of multiple novel datasets (i.e., DNA seq, glycomics, epigenetics, metagenomics, etc.). To start with, the two-way orthogonal partial least squares (O2PLS) method will be considered, in which two datasets can be decomposed in three subspaces, namely a common, an systematic (or independent) and a residual subspace. Three main objectives are: 1) Designing high-quality simulations that reflect the complex situations involving multiple omics datasets, 2) Extending O2PLS to a probabilistic model, and 3) Determining the size of the common subspace. Further information about the research is available here .
You will interact and develop research collaborations with our IMforFUTURE academic partners, and in addition you’ll participate in activities of the Innovative Training Network, including attending training courses and visiting other sites.
The Julius Center is one of twelve divisions of the UMC Utrecht. Its mission is to contribute to the scientific knowledge base of medical practice by initiating and conducting high-quality applied medical research and by providing high-quality education covering the area from bachelor to post-graduate teaching programs. The departments of the Julius Center are Epidemiology, Primary Care, PHM (Public health, Healthcare Innovation and Evaluation, and Medical Humanities), and Biostatistics & Research Support. Its research programs cover four areas: Cardiovascular Diseases, Infectious Diseases, Cancer, and Methodology. The division also supports the design, conduct, analyses, and reporting of clinical research in virtually all departments of the UMC Utrecht. The department of Biostatistics and Research Support has two main focus areas of research, ‘methodology for high dimensional (big) data’ and ‘clinical trials methodology’. The department provides statistical education within a number of bachelor and master programs a.o. from the Faculty of Medicine of Utrecht University.
You are expected to have a very strong academic record, including a master degree (or overseas equivalent) in statistics, biostatistics, mathematics or quantitative science. You have excellent statistical programming skills and the ability to work independently. You are confident about working in an multidisciplinary environments. You’ll also have excellent communication and organisational skills and a strong commitment to your own professional development. You must not have resided or carried out your main activity (work, studies, etc.) in the Netherlands for more than twelve months in the three years immediately prior to your employment with us. You are in the first four years (full-time equivalent research experience) of your research career and have not been awarded a doctoral degree.
The maximum salary for this position (100%) is € 2.919,00 gross per month based on full-time employment (work week 36 hours). This job is based on a temporary position for 36 months.
In addition, we offer an annual benefit of 8.3%, holiday allowance, travel expenses, career opportunities and personal budget. The terms of employment are in accordance with the Cao University Medical Centers (UMC).
The contract will be for one year with possibility of extension to three years.
If you have any questions about this vacancy, please contact Mrs.Dr HW Uh, Assistant Professor, phone 0887568635. Email H.W.Uh@umcutrecht.nl.
Acquisition based on this jobopening is not appreciated.