Biostatistician - Benguerir

Position Overview

The Biosciences CoreLab is seeking a skilled and motivated Biostatistician to support the statistical analysis and interpretation of complex biological and omics data.

The successful candidate will work closely with researchers, laboratory scientists, bioinformaticians, and other collaborators to ensure that appropriate statistical methods are applied throughout the research process - from experimental design and data processing to analysis, visualization, interpretation, and reporting.

Key Responsibilities

• Provide statistical support for biological, biomedical, and life-sciences research projects.
• Contribute to study design, sample-size estimation, power calculations, and the development of statistical analysis plans.
• Analyze complex biological datasets, including high-dimensional, omics, and large-scale data.
• Apply appropriate statistical and computational methods to genomics, transcriptomics, proteomics, metabolomics, and other omics datasets.
• Develop, implement, and validate statistical models and reproducible data-analysis pipelines.
• Perform exploratory data analysis, multivariate analysis, hypothesis testing, regression analysis, survival analysis, and predictive modeling, as required.
• Generate clear and accurate data visualizations, reports, and analytical summaries.
• Interpret results in collaboration with scientists and translate complex findings into meaningful biological insights.
• Ensure data quality, analytical reproducibility, and proper documentation of methods, code, and results.
• Contribute to scientific publications, technical reports, presentations, and research protocols.
• Stay informed about emerging statistical methodologies, computational tools, and best practices in biostatistics and omics data analysis.
• Provide guidance or training to researchers and laboratory staff on statistical concepts and data-analysis practices.

Required Qualifications

• Master's degree in Biostatistics, Statistics, Applied Mathematics, Data Science, Bioinformatics, Computational Biology, or a closely related discipline.
• A PhD in one of these fields is considered an advantage.
• At least two years of relevant experience in biostatistics, biological data analysis, bioinformatics, or a related research environment.
• Strong knowledge of statistical methodologies and their application to biological or biomedical research.
• Solid background in omics data analysis and high-dimensional or large-scale datasets.
• Proficiency in statistical programming using R and/or Python.
• Experience with statistical software, data visualization tools, and reproducible research workflows.
• Good understanding of experimental design, data-quality assessment, and statistical interpretation.
• Ability to communicate statistical concepts and analytical results clearly to both technical and non-technical audiences.
• Strong analytical thinking, attention to detail, and problem-solving skills.
• Ability to work independently while collaborating effectively within multidisciplinary teams.

Preferred Qualifications

• Experience working in a genomics, biosciences, clinical research, or core laboratory environment.
• Familiarity with next-generation sequencing data, multi-omics data, and related analytical workflows.
• Experience integrating multiple types of omics data.
• Knowledge of machine learning and predictive modeling applied to biological data.
• Familiarity with version-control tools such as high-performance or cloud-computing environments.
• Previous contribution to peer-reviewed scientific publications.
• Experience supporting multiple research projects and managing competing priorities.

Key Competencies

• Scientific rigor and critical thinking
• Statistical and computational expertise
• Effective communication and collaboration
• Data-driven problem-solving
• Accuracy and attention to detail
• Organization and time management
• Commitment to data integrity and reproducible research