The Luxembourg Centre for Systems Biomedicine (LCSB) is looking for a machine learning expert / bioinformatician 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 machine learning 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.
- 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 Profile:
- The candidate will have a PhD or equivalent degree in machine learning, statistcs 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 Centre 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.
Further Information:
Applications should contain the following documents (ideally combined into one pdf document):
- A detailed Curriculum vitae
- A motivation letter, including a brief description of past research experience and future interests, as well as the earliest possible starting date
- Copies of degree certificates and transcripts
- Optional: Name and contact details of at least two referees
Please apply online until via the following link: http://emea3.mrted.ly/11qq2
