Bioinformatics Engineer - Virtual Cells

Antler; Greater London; On-site; GBP 60,000 - 85,000; Full time

Job summary

An innovative biology AI lab is seeking a candidate to focus on virtual cell modeling related to neurological diseases in London, UK. This role involves developing experimental hypotheses, analyzing multi-omic datasets, and collaborating with research partners. The ideal candidate should have strong data engineering and software skills in relevant tools like NextFlow and AWS. This opportunity promises personal and professional growth, applying AI approaches to real-world biological challenges.

Qualifications

• Experience with generating biological insights from multi-omic data.
• Hands-on exposure to perturbation datasets and state transitions.
• Ability to write high-quality code for data processing.

Responsibilities

• Create experimental hypotheses for neurological diseases.
• Curate and analyze datasets for data modeling.
• Develop and manage research collaborations.

Skills

Cellular state representation

Multi-omic data analysis

Data engineering

Statistical approaches

Software engineering

Tools

NextFlow

AWS

Python

Spark

Hadoop

Job description

About Prima Mente

Prima Mente is a frontier biology AI lab. We generate our own data, build general purpose biological foundation models, and translate discoveries into research and clinical outcomes. Our first goal is to tackle the brain: to deeply understand it, protect it from neurological disease, and enhance it in health. Our team of AI researchers, experimentalists, clinicians, and operators is based in London, San Francisco and Dubai.

Role focus - Virtual Cells

Clearly articulate and interrogate meaningful biological hypotheses for marker and target discovery related to neurological diseases, via a virtual cell model.

Key Tasks

• Set up and framework experimental hypotheses focussed on available datasets and models, with downstream evaluation criteria to assess performance.
• Identify and curate public and proprietary datasets across different multi-omic, multi-modal types.
• QC and data analysis.
• Multi-omic bioinformatics pipeline development.
• Feature engineering and dataset preparation for downstream machine learning as well as foundational AI training and application.
• Work with experimental and machine learning teams to confirm and refine computational findings.
• Develop and manage specific external research collaborations with academic and industrial partners specific to AD biology.

Expected Growth

In 1 month you will be responsible for your own analysis and experiments on our cloud compute environment, involving creating an ad hoc nextflow or flyte workflow to massively process your data.

In 3 months you directly own and have created an optimised analysis or data processing pipeline and generated results fit for patent and publication.

In 6 months you have integrated your research into our AI models.

Who You Are

We are seeking strong experience representing cellular state from transcriptomic and/or multi-omic data. Right now, we prefer candidates with hands‑on exposure to perturbation datasets and methods for modeling state transitions (e.g., how a cell moves from one state to another). Familiarity with encoders and probabilistic/distributional modeling is a plus, but not required. Most important is a strong, practical understanding of cellular state change and how to leverage it to study and explain disease.

We don’t expect you to check every box. Strong applicants often have depth in some of these and interest in growing into others.

Ideal experience

• Top tier publications.
• Patent experience.
• First‑hand experience with generating biological insights from biological data for virtual cells (genomics, epigenetics, transcriptomics, proteomics, ATAC‑Seq).
• Operational software engineering skills: the ability to write high‑quality code to be the backbone of our software stack.
• Experience with end‑to‑end tools used to process multi‑omic data from raw data all the way to analytical outputs. Good working knowledge of workflow managers, including but not limited to NextFlow.
• Expertise with statistical approaches applied to evaluating biological datasets.
• Strong working knowledge with cloud computing environments, including but not limited to AWS.
• Domain knowledge with advanced artificial intelligence approaches and experience applying them to a biological context.
• Familiar with data wrangling, analysis, and visualisation libraries using Python (preferable), R or Julia.
• Strong data engineering knowledge, including but not limited to experience with Spark, Hadoop, NoSQL.

Location

Based in San Francisco, US or London, UK. We support O1 (US) and GTV (UK) visa applications.

Culture Insight

What we are doing is extremely hard. Prima Mente is for great people. We are team players who appreciate challenges, want to be hands‑on, and thrive on curiosity by throwing away assumptions. We are focused on excellence at pace and huge personal growth. We are strong communicators who are highly disciplined and rigorous.

Prima Mente operates with a flat organizational structure. We gain and share knowledge by contributing to multiple opportunities. Leadership is given to those who show initiative and consistently deliver excellence.

We arrange our lives so we can work in person as much as possible.

Our Values

Exceptional performance at exceptional pace

• The solutions we build demand uncompromising quality and rigour.
• The problems we are solving are grave and present.

Inquisitive discovery

• We embrace curiosity and creativity.
• Every question is a path to a transformational breakthrough.

Radical candour

• We practice unwavering honesty and transparency in all our challenges and interactions.

Purposeful individuality

• Every individual in our team is celebrated for their identity, uniqueness, and experiences.
• We are invested in each one’s bespoke personal development.
• Nurturing individuality will supercharge our collective purpose and spirit.

Patient impact at scale

• We have a steadfast commitment to improve the health and well‑being of patients globally.
• Every experiment run, every dataset analysed, and every innovation developed, is a step towards achieving a scalable impact.