About the LCSB The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Luxembourg Centre for Systems Biomedicine (LCSB) is an interdisciplinary research centre of the University of Luxembourg. We conduct fundamental and translational research in the field of Systems Biology and Biomedicine in the lab, in the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer''s and Parkinson''s disease and their contributing factors. The LCSB recruits talented scientists from various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated biostatistician or computational biologist who is well versed in the statistical and machine learning analysis of biomedical data and bioscientific programming for projects on neurological and cancer diseases. The candidate should have experience in the analysis of large scale biomedical data (omics, clinical or other large scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single cell omics and clinical data to predict clinical outcomes of interest and therapeutics. This will include implementing and applying software analysis pipelines and interpreting disease related data together with experimental and clinical collaborators. With the help of statistics, machine learning and pathway and network and analyses, the goal is to improve the mechanistic understanding of disease and treatment associated alterations in complex neurological and cancer disorders. Your profile The candidate will have an MSc or equivalent degree in biostatistics, bioinformatics, computational biology, machine learning, or related subject areas Prior experience in large scale data processing and statistics / machine learning is required Previous work and publications in bioinformatics analysis of large scale biomedical data (e.g., omics, clinical, structural bioinformatics, other biomedical data) should be outlined in the CV Demonstrated skills and knowledge in omics data analysis, biostatistics, machine learning, pathway and network analysis are highly advantageous Experience with analysis of epigenetic data (e.g. ATAC seq, ChIP seq) is a plus Familiarity with both cancer and neurodegenerative disease biology is beneficial 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 Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Me