Scientist, Computational Biology Innovation Hub

Altos Labs; Cambridge; On-site; GBP 40,000 - 70,000; Full time

Job summary

A leading biotechnology company in Cambridge seeks a Computational Scientist/Biologist for its Bioinformatics Innovation Hub. Candidates should possess a PhD in a quantitative field or life sciences, extensive multi-modal data analysis experience, and proficiency in programming languages like Python and R. This role involves collaboration on cellular rejuvenation projects and developing advanced data analytic methods. Strong communication and teamwork skills are essential for success.

Qualifications

• PhD in computational biology, mathematics, physics or life sciences with computational experience.
• Extensive knowledge of multi-modal data analysis required.
• Strong expertise with various NGS workflows like RNA-seq and ChIP-seq.

Responsibilities

• Collaborate with experts to design studies on cellular health.
• Develop statistical, ML, and AI methods for analysis.
• Produce visualisations of complex analyses in reports.

Skills

Multi-modal data analysis

Collaboration

Communication skills

Statistical analysis

Proficiency in Python

Proficiency in R

Education

PhD in a quantitative field or life sciences

Tools

Python packages (Pandas, Scikit-learn)

R packages (Tidyverse, Caret)

Linux

Job description

Computational Scientist/Biologist, Bioinformatics Innovation Hub

Cambridge, UK

Overview

The Bioinformatics Innovation Hub is a cross-Altos team working on challenging and exciting scientific projects and cutting edge technologies, requiring both the development and implementation of data processing workflows and advanced analytics of multi-modal datasets 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, computational and data scientists, as well as AI experts.

Responsibilities

• Collaborate closely with domain knowledge experts to plan and design studies to elucidate molecular phenotypes of cellular health, rejuvenation and reprogramming
• Focus on FAIR data principles in the processing of internal and external NGS sequencing data, data organisation and metadata capture to enable efficient downstream data consumption
• Generate insights and models from multi-omics datasets to understand patterns, trends and relationships within data to inform decision-making and solve problems.
• Develop and implement state of the art statistical, ML and AI methods for large scale data processing and analysis
• Produce informative visualisations of complex analyses and embed these in automated and bespoke reports and interactive dashboards
• Partner with other scientists to establish automated, robust and efficient analytical pipelines for reproducible research and to champion the integration of data science into biological discovery
• Work with IT and data engineering teams to run analyses at scale in high-performance computing and cloud environments
• Stay current with and adopt emergent analytical methodologies, tools and applications to ensure fit-for-purpose and impactful approaches

Who You Are

We are looking for a strong team player who will be working on a range of projects across the scientific questions central to the Altos mission. Working in a highly collaborative environment, the ideal candidate will be able to quickly understand the biological background of a project, apply their bioinformatics, data analysis and statistical skills, and be able to communicate results clearly and concisely. We are looking for an individual who can not only respond to requests but will also show initiative in complex analytical tasks, take forward a project independently and show ownership of the work done. They should also demonstrate a strong willingness to learn and develop.

The successful candidate will have strong expertise with various NGS workflows and data types such as RNA-seq, ATAC-seq, ChIP-seq, Perturb-seq, etc., be familiar with single cell technologies and have previous experience with integration of multi-modal omics data.

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 multi-modal data analysis
• Proficiency in Python and/or R, Linux. 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 organisational skills and the ability to work independently
• Familiarity with databases/resources relevant to drug discovery

Preferred Qualifications

• Knowledge of single-cell sequencing technologies and analytical techniques
• Experience with Nextflow
• Experience with long read sequencing (Nanopore, PacBio)
• Experience with cloud providers (e.g. AWS)
• Background in cellular rejuvenation and reprogramming
• Familiarity with publicly available single cell data resources

Equal Opportunity Employment

Altos Labs provides equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Altos prohibits unlawful discrimination and harassment. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.