Introduction
The University of Luxembourg has the following vacancy in the Luxembourg Centre for Systems Biomedicine (LCSB, http://wwwen.uni.lu/lcsb). The LCSB is accelerating biomedical research by closing the link between systems biology and medical research. Collaboration between biologists, medical doctors, computer scientists, physicists and mathematicians is offering new insights in complex systems like cells, organs, and organisms. These insights are essential for understanding principal mechanisms of disease pathogenesis and for developing new tools in diagnostics and therapy.
The National Centre of Excellence in Research on Parkinson’s disease is a recently launched 8-year program, which involves all national actors in biomedical research in Luxembourg. One long-term objective of program is to recruit and analyze a cohort of PD patients from Luxembourg and clinical centers in neighboring countries to help identify predictive and progressive biomarkers of the disease. Systems biological tools, in particular state-of-the-art computational modeling, will be used for biomarker identification. International partners in this program include the Oxford Parkinson’s Disease Centre, the Hertie-Institut für klinische Hirnforschung in Tübingen, the Paracelsus-Elena-Klinik in Kassel, and the National Institutes of Health in the USA.
Research Associate (Postdoctoral fellow) in Machine Learning / Bioinformatics (m/f)
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Fixed-term contract 2 years, 40h/week, may be extended up to 5 years.
Employee status (start date: as soon as possible)
Ref.: I1R-BIC-PFN-15NCER
Your Role:
We are looking for a bioinformatician or machine learning expert who is well versed in the statistical analysis of large-scale biological data and bioscientific programming. The candidate will be responsible for the processing and biomedical analysis of RNA sequencing, microarray and GWAS data, and the collaborative integration of analysis results with those obtained on clinical, proteomics and metabolomics data. The project is part of a long-term, multi-centre collaboration on diagnostic biomarker discovery for Parkinson’s disease patients. It will use both existing and newly collected high-throughput experimental data from patients and controls, but also from corresponding in vivo and in vitro models as part of an integrative systems biology approach.
Your Profile:
• The candidate will have a PhD or equivalent degree in machine learning or bioinformatics
• Prior experience in large-scale data processing and bioscientific programming is required
• A track record of previous publications in large-scale biological data analysis should be outlined in the CV
• Demonstrated skills and knowledge in machine learning, biostatistics, next-generation sequencing data analysis (in particular RNAseq), pathway and network analysis are highly advantageous
• The candidate should have a cross-disciplinary aptitude, strong organizational and interpersonal skills, and a keen interest in collaborative biomedical research
• Fluency in oral and written English
We offer:
• A fully funded position with a very competitive salary.
• An opportunity to join the National Center of Excellence in Research on Parkinson’s disease with an international and interdisciplinary ethos.
• Working in a scientifically stimulating, innovative, dynamic, well- equipped, and international surrounding.
• Opportunity to work closely with worldwide academic partners.
• The University offers highly competitive salaries based on the candidate's experience and is an equal opportunity employer.
Further Information:
Applications (in English) should contain the following documents:
• A detailed Curriculum vitae
• A motivation letter, including a brief description of past research experience and future interests
• Copies of degree certificates and transcripts
• Name and contact details of at least two referees
Further Information:
Recruitment web-page: http://goo.gl/33STL4
How to Contact/Apply
Informal enquiries can be made to:
Dr. Enrico Glaab: enrico.glaab@uni.lu
Deadline
Applications can be submitted apply online until 30th September 2016.
Apply Online
Apply
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