We seek a highly motivated bioinformatician who is experienced in the analysis of large-scale biomedical omics data, using statistical methods and machine learning, and bioscientific data processing and programming. The candidate will conduct integrative stratification analyses of biomedical data, focusing on molecular, clinical and neuroimaging data for neurodegenerative diseases. This will include the review, set-up and application of software analysis pipelines, and the joint interpretation of disease-related data together with experimental and clinical collaborators. The project will use new biological high-throughput data from patients, healthy controls, as well as in-vitro and in-vivo disease models. With the help of pathway-, network- and machine learning analyses, the goal is to improve the mechanistic understanding of molecular and cellular perturbations in common neurological disorders.
• The candidate will have a PhD or equivalent degree in bioinformatics or computational biology
• Prior experience in large-scale data processing and statistics / machine learning is required
• A track record of previous publications in bioinformatics analysis of large-scale biological data (e.g. omics, neuroimaging data) should be outlined in the CV
• Demonstrated skills and knowledge in next-generation sequencing data analysis, biostatistics, machine learning, 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
• A fully funded position with a highly 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.
• State-of-the-art research facilities and computational equipment
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
• Name and contact details of at least two referees
For further information, please contact:
Enrico Glaab (firstname.lastname@example.org)