What You Will Contribute To Altos

The Bioinformatics Innovation Hub is a cross-Altos team of computational scientists working across the three institutes in San Diego, San Francisco and Cambridge (UK). This position is not tied to any specific site.

The bioinformatics team is working on challenging and exciting scientific projects requiring both the development and implementation of data processing workflows and bespoke advanced analytics to unravel the molecular mechanisms underlying cellular rejuvenation and reprogramming. We expect the candidate to apply rigorous scientific thinking and robust methods, and furthermore have strong work ethics. They will work closely with a cross-disciplinary team including domain knowledge experts, data generation experts and other computational scientists.

With this position we aim to strengthen the team in spatial omics.

Responsibilities

• Interact closely with the Genomics and Imaging Hubs on developing and running spatial omics workflows, contribute to solutions for data storage, pre-processing and analysis of Xenium data, act as a point of contact for experimentalists regarding spatial omics experiments
• Collaborate closely with domain knowledge experts to plan and design studies to elucidate molecular phenotypes of cellular health, rejuvenation and reprogramming
• Process internal and external NGS sequencing data according to Altos’ standards
• Independently analyze internal and external NGS sequencing data
• Integrate different Omics data types using state-of-the-art statistical models
• Analyze 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
• Embed analyses and visualizations in automated and bespoke 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 PhD in the life sciences with significant computational experience
• Extensive knowledge of NGS data analysis
• Experience with spatial transcriptomics
• Experience with implementing workflows using Nextflow
• Proficiency in Python and/or R. Hands-on skills using data science packages (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

• Knowledge of single-cell sequencing technologies and analytical techniques
• Experience with variant calling methodologies
• Experience with long read sequencing (Nanopore, PacBio)
• Experience with cloud providers (e.g. AWS)
• Comfortable working in command line/Linux environments
• Background in cellular rejuvenation and reprogramming
• Familiarity with publicly available single cell data resources

The salary range for Cambridge, UK:

• Scientist I, Computational Biology: £52,700 - £74,400
• Scientist II, Computational Biology: £62,000 - £90,000
• Senior Scientist I, Computational Biology: £72,000 - £112,500

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.