Bioinformatician (Spatial & Single-Cell) in London

Bioinformatician (Spatial & Single-Cell) in London

London Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Deep Science Ventures

At a Glance

  • Tasks: Design and build bioinformatics pipelines for cutting-edge drug discovery.
  • Company: StealthCo, a pioneering techbio startup focused on computational drug discovery.
  • Benefits: Competitive pay, equity options, flexible work arrangements, and high autonomy.
  • Other info: Remote-first culture with minimal management and direct influence on projects.
  • Why this job: Join a small, innovative team making a real impact in oncology research.
  • Qualifications: PhD in relevant field and experience with bioinformatics pipelines.

The predicted salary is between 60000 - 80000 £ per year.

StealthCo is a seed‑stage techbio company, created within DSV, building a computational drug discovery platform that constructs causal biological networks from large‑scale primary human single‑cell omics data and structured published experimental literature. Our multi‑agent AI system reasons over these networks to generate, simulate, and rank mechanistic hypotheses for combination therapies – with system accuracy verified against top‑tier researchers at the Allen Institute. We will initially focus on oncology indications.

The Role (remote, timezone-restricted)

You will design and build production bioinformatics pipelines for new modalities—spatial transcriptomics, single‑cell proteomics, and spatial proteomics—extending our existing scRNA‑seq infrastructure. These pipelines feed directly into an agentic hypothesis generation system: the quality of what goes in determines the quality of every therapeutic hypothesis that comes out.

You’ll Work Closely With Our Head Of AI & Technology (Dr. Francesco Moramarco) And Head Of Platform (Dr. Moustafa Khedr) To:

  • Build end‑to‑end pipelines (ingestion, QC, normalisation, integration, annotation, differential analysis)
  • Design modality‑specific statistics: spot deconvolution, spatial autocorrelation, ADT normalisation, protein‑RNA joint embedding, segmentation, spillover correction
  • Extend hierarchical cell type annotation across modalities
  • Codify best‑practice workflows into reusable templates for agent execution
  • Sanity‑check outputs to catch batch effects and artefacts before they propagate

Requirements:

  • PhD in computational biology, bioinformatics, genomics, systems biology, or related quantitative field
  • 2–6 years experience in early‑stage/high‑growth startups
  • Pipeline‑building experience with spatial transcriptomics (Visium, MERFISH, Xenium) from scratch
  • Experience with single‑cell or spatial proteomics (CITE‑seq, CyTOF, CODEX, IMC)
  • Strong Python engineering in the anndata ecosystem (scanpy/squidpy/muon)
  • Deep single‑cell & spatial statistics knowledge (pseudobulk, multiple testing correction, mixed‑effects models, compositional analysis)
  • Strong biology grounding; can distinguish biology vs confound; assess mechanistic plausibility
  • Timezone: at least 5 hours overlap with UK working hours (UTC−4 through UTC+4 preferred)

Strong desirables:

  • Tumour biology / cancer immunology (TME, immune evasion, resistance)
  • Comfort working in an AI‑mediated workflow and writing analysis plans executed by agents
  • Experience building pipelines/tools consumed by others; cloud compute (GCP preferred); R proficiency

Nice to have:

  • Wet lab experience and familiarity with the 10x Genomics ecosystem

We know job descriptions like this can read as a wish list. If you don’t tick every box, but believe you can build what we need – apply anyway! We care more about what you’ve built and how you think than whether your CV maps perfectly to every bullet point.

Benefits:

  • Competitive compensation commensurate with experience and profile, plus equity participation.
  • Flexible arrangement depending on location and preference (full‑time employment or long‑term consultancy).
  • Small, technically intense team with high autonomy and ownership.
  • Remote‑first. Minimal management layers and direct impact on decisions.

Bioinformatician (Spatial & Single-Cell) in London employer: Deep Science Ventures

StealthCo is an exceptional employer for bioinformaticians, offering a unique opportunity to work at the forefront of computational drug discovery within a small, innovative team. With a remote-first culture that prioritises flexibility and autonomy, employees can directly influence impactful decisions while enjoying competitive compensation and equity participation. The company fosters a collaborative environment with strong mentorship from leading experts, ensuring ample opportunities for professional growth in a cutting-edge field focused on oncology.

Deep Science Ventures

Contact Details:

Deep Science Ventures Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Bioinformatician (Spatial & Single-Cell) in London

Network Like a Pro

Get out there and connect with folks in the bioinformatics scene! Attend meetups, webinars, or even online forums. The more people you know, the better your chances of landing that dream job.

Show Off Your Skills

Don’t just tell them what you can do; show them! Create a portfolio of your projects, especially those related to spatial transcriptomics or single-cell proteomics. This will give potential employers a taste of what you can bring to the table.

Ace the Interview

Prepare for interviews by brushing up on your technical knowledge and being ready to discuss your past experiences. Practice common interview questions and think about how your skills align with what StealthCo is looking for.

Apply Through Our Website

We encourage you to apply directly through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at StealthCo.

We think you need these skills to ace Bioinformatician (Spatial & Single-Cell) in London

Bioinformatics Pipeline Design
Spatial Transcriptomics
Single-Cell Proteomics
Python Engineering
Anndata Ecosystem (Scanpy/Squidpy/Muon)
Deep Single-Cell Statistics
Tumour Biology

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the role of a Bioinformatician. Highlight your pipeline-building experience and any relevant projects you've worked on, especially in spatial transcriptomics or single-cell proteomics.

Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about bioinformatics and how your background makes you a great fit for our team. Don’t just repeat your CV; share stories that showcase your problem-solving skills and creativity in building pipelines.

Showcase Your Technical Skills:We want to see your technical prowess! Include specific examples of your Python engineering skills, particularly within the anndata ecosystem. If you've worked with cloud computing or AI workflows, make sure to mention that too!

Apply Through Our Website:We encourage you to apply directly 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 us you’re keen on joining our team!

How to prepare for a job interview at Deep Science Ventures

Know Your Bioinformatics Inside Out

Make sure you brush up on your knowledge of spatial transcriptomics and single-cell proteomics. Be ready to discuss specific techniques you've used, like Visium or CITE-seq, and how they relate to the role. This shows you're not just familiar with the terms but have hands-on experience.

Showcase Your Pipeline-Building Skills

Prepare to talk about your previous experiences in building bioinformatics pipelines from scratch. Highlight any challenges you faced and how you overcame them. This will demonstrate your problem-solving skills and your ability to contribute to their agentic hypothesis generation system.

Understand the Company’s Focus

Research StealthCo's work in oncology and their computational drug discovery platform. Being able to discuss their approach to causal biological networks and how your skills can enhance their projects will show that you're genuinely interested and aligned with their mission.

Be Ready for Technical Questions

Expect to dive deep into technical discussions, especially around Python engineering and statistical methods. Brush up on concepts like mixed-effects models and compositional analysis, as these are crucial for the role. Practising explaining these concepts clearly will help you stand out.