We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning analysis of biomedical data and bioscientific programming for a project on the study of neurological disorders. The candidate should have experience in the analysis of large-scale biomedical data (omics, clinical or neuroimaging data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on omics, neuroimaging and clinical data to predict prognostic outcomes of interest (clinical progression, worsening of morphometry and connectivity patterns in brain MRI). This will include implementing and applying software analysis pipelines and interpreting disease-related data together with experimental and clinical collaborators. Classification models guided by prior mechanistic knowledge will be built, exploiting the known grouping structures among features in the omics and neuroimaging data, using dedicated structured learning algorithms. With the help of statistics, machine learning and pathway- and network- and analyses, the goal is to improve the mechanistic understanding of disease-associated alterations in neurological disorders.
• 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
• The candidate will have a MSc or equivalent degree in bioinformatics, computational biology, biostatistics, machine learning, or related subject areas
• Prior experience in large-scale data processing and statistics / machine learning is required
• Publications in bioinformatics analysis of large-scale biomedical data (e.g. omics, clinical, structural bioinformatics, neuroimaging data) should be outlined in the CV
• Demonstrated skills and knowledge in MRI or NGS 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
Applications should contain the following documents (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: