Computational Biologist, Single Cell Omics Data Analysis

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

As a member of the multi-omics data integration team, you will lead the development and application of advanced analytics methods to unravel the molecular mechanisms underlying cellular rejuvenation and reprogramming. In this role, you will focus on inferring gene regulatory networks, studying cell-cell interactions and understanding how these modulate cell state dynamics. You will work with diverse types of single cell data including scRNA-Seq, scATAC-Seq, scChIP-seq, Perturb-Seq and scProteomic data.

The ideal candidate will enjoy working on a wide range of interesting problems, be involved in all aspects of a research project and develop robust computational tools and pipelines for data processing and analysis. The successful candidate will demonstrate rigorous scientific thinking, strong work ethic and the ability to work equally well in a team or independently. They will work closely with a cross-disciplinary team including domain knowledge experts, data generation experts and other computational scientists.

• Collaborate closely with domain knowledge experts to plan and design studies to elucidate molecular phenotypes of cellular health, rejuvenation and reprogramming 
• Build pipelines for the analysis of single cell data covering the entire workflow from raw data to read/counts, data normalization and transformation, dimensionality reduction, cluster analysis, differential expression, trajectory analysis, enrichment analysis
• Develop workflows for single cell data integration using state-of-the-art statistical and machine learning models
• Embed analyses and visualizations in automated reports
• Build interactive dashboards for data visualization and exploration
• Partner with other computational scientists to establish automated, robust and efficient analytical pipelines for reproducible research
• Stay current with and adopt emergent analytical methodologies, tools and applications to ensure fit-for-purpose and impactful approaches

Who You Are

Minimum Qualifications

• PhD in a quantitative field (e.g. computational biology, mathematics, physics) with significant biological background OR a Life Science degree with significant computational experience
• Extensive knowledge of single cell analysis tools and methods
• Proficiency in Python and/or R. Hands-on skills using data science packages (for instance, Pandas, Scikit-learn, NumPy, Tidyverse, Caret).
• Statistical analysis background 
• Excellent communication skills. Ability to present complex computational methods to non-experts. 
• Established ability to translate biologists/project team’s scientific questions into analytical strategies and methods.
• Strong collaboration skills and ability to work as part of a team in an international and interdisciplinary environment.
• Outstanding organizational skills and the ability to work independently.

Preferred Qualifications

• Experience with Nextflow 
• Background in cellular rejuvenation and reprogramming 
• Familiarity with publicly available single cell data resources