We are looking for a bioinformatician and biostatistics 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 analysis of genetic and functional omics data, including integrative pathway/network analysis and building and evaluating machine learning models. The project is part of a multi-centre collaboration on the omics-based stratification of Parkinson’s disease patients for developing personalized therapeutic interventions with partners in Germany and France.
We offer
• A fully funded position with a very competitive salary.
• An opportunity to join the Luxembourg Centre of Systems Biomedicine with an international and interdisciplinary ethos.
• Working in a scientifically stimulating, innovative, dynamic, well- equipped, and international surrounding.
• Opportunity to work closely with international academic partners.
Your Profile
• The candidate will have a PhD or equivalent degree in bioinformatics, biostatistics or related subject areas (e.g. machine learning with applications in genetic and molecular data analysis)
• 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 biostatistics, machine learning, GWAS or next-generation sequencing data analysis, and 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
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 two or more referees
For further information, please contact:
Enrico Glaab, enrico.glaab@uni.lu