Bioinformatician - Computational Biology

About the Role

Our client is looking for a skilled Bioinformatician to join their computational biology team in Edinburgh . This hybrid role focuses on leveraging large-scale biological datasets to uncover new insights into disease mechanisms and drug targets. You will work closely with experimental biologists and data scientists, applying advanced computational techniques to analyze genomics, transcriptomics, and proteomics data. This is an exciting opportunity for a technically adept individual to contribute to innovative research in a collaborative and forward-thinking environment.

Key Responsibilities

• Develop and implement computational pipelines for the analysis of high-throughput biological data (e.g., NGS, RNA-Seq, proteomics).
• Perform statistical analysis and machine learning on complex biological datasets to identify significant patterns and biomarkers.
• Collaborate with experimental scientists to design studies and interpret results from a computational perspective.
• Develop and maintain databases and data management systems for research projects.
• Create visualizations and reports to effectively communicate findings to both technical and non-technical audiences.
• Stay updated with the latest advancements in bioinformatics tools, algorithms, and biological data analysis techniques.

Requirements

• Ph.D. or Master's degree in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related field.
• Proven experience in analyzing large biological datasets, such as genomics, transcriptomics, or proteomics data.
• Proficiency in programming languages commonly used in bioinformatics, such as Python or R, and associated libraries (e.g., Biopython, SciPy).
• Experience with scripting languages (e.g., Bash) and working in a Linux/Unix environment.
• Familiarity with statistical modeling and machine learning techniques.
• Strong communication skills and the ability to work effectively in a multidisciplinary team.

Benefits

• Competitive salary and annual bonus.
• Hybrid working model offering flexibility.
• Comprehensive private health insurance and wellness programs.
• Generous contribution to a pension plan.
• Support for attending scientific conferences and professional development.