Scientist, Computational Biology Innovation Hub in Cambridge

Scientist, Computational Biology Innovation Hub in Cambridge

Cambridge Full-Time 30000 - 50000 £ / year (est.) No working from home possible
Altos Labs

At a Glance

  • Tasks: Collaborate on innovative projects in computational biology and data analysis.
  • Company: Join a cutting-edge Bioinformatics Innovation Hub in Cambridge.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on collaboration and learning.
  • Why this job: Make a real impact on cellular rejuvenation and reprogramming research.
  • Qualifications: PhD in a quantitative field or life sciences with computational experience.

The predicted salary is between 30000 - 50000 £ per year.

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.

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Scientist, Computational Biology Innovation Hub in Cambridge employer: Altos Labs

At Altos Labs, we pride ourselves on being an exceptional employer, fostering a collaborative and innovative work culture in the heart of Cambridge. Our commitment to employee growth is evident through our support for continuous learning and development, while our cutting-edge projects in computational biology offer unique opportunities to contribute to groundbreaking scientific advancements. Join us to be part of a diverse team that values rigorous scientific thinking and encourages initiative, all within a vibrant and inclusive environment.

Altos Labs

Contact Details:

Altos Labs Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Scientist, Computational Biology Innovation Hub in Cambridge

Tip Number 1

Network like a pro! Reach out to people in the field, attend relevant meetups or conferences, and don’t be shy about introducing yourself. You never know who might have the inside scoop on job openings or can put in a good word for you.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those involving multi-omics datasets or advanced analytics. This will give potential employers a taste of what you can do and set you apart from the crowd.

Tip Number 3

Prepare for interviews by brushing up on your communication skills. Be ready to explain complex concepts in simple terms, as you’ll likely need to collaborate with non-experts. Practice makes perfect!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at the Bioinformatics Innovation Hub.

We think you need these skills to ace Scientist, Computational Biology Innovation Hub in Cambridge

Computational Biology
Bioinformatics
Data Processing Workflows
Multi-Omics Data Analysis
Statistical Methods
Machine Learning
Artificial Intelligence

Some tips for your application 🫡

Show Your Passion:When writing your application, let your enthusiasm for computational biology shine through! We want to see how excited you are about the projects we’re working on and how your skills can contribute to our mission.

Tailor Your CV:Make sure your CV is tailored to highlight your relevant experience in bioinformatics and data analysis. We love seeing specific examples of how you've tackled complex problems or collaborated with teams in the past.

Be Clear and Concise:In your cover letter, keep it clear and concise. We appreciate straightforward communication, so focus on your key achievements and how they relate to the role. Avoid jargon unless it’s absolutely necessary!

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join our team at StudySmarter!

How to prepare for a job interview at Altos Labs

Know Your Data Inside Out

Make sure you’re well-versed in the various NGS workflows and data types mentioned in the job description. Brush up on RNA-seq, ATAC-seq, and other relevant techniques so you can confidently discuss your experience and how it relates to the projects at the Bioinformatics Innovation Hub.

Showcase Your Collaboration Skills

Since this role involves working closely with a cross-disciplinary team, be prepared to share examples of past collaborations. Highlight how you’ve effectively communicated complex ideas to non-experts and how you’ve contributed to team success in previous projects.

Demonstrate Your Analytical Thinking

Prepare to discuss specific analytical strategies you've employed in past projects. Be ready to explain how you translated scientific questions into actionable data analysis methods, showcasing your problem-solving skills and initiative.

Stay Current with Trends

Familiarise yourself with the latest methodologies and tools in computational biology and bioinformatics. Mention any recent advancements or tools you’ve adopted in your work, as this shows your commitment to staying at the forefront of the field.