Data Scientist/ Senior Data Scientist P Znamenskiy lab

The Francis Crick Institute
London
5 days ago
Create job alert

Description

:

Data Scientist/Senior Data Scientist - P Znamenskiy lab

Reporting to: Petr Znamenskiy, Group Leader (The Francis Crick Institute)

Contact term: This is a full-time, fixed term (3-year) position on Crick terms and conditions of employment.

About us

The Francis Crick Institute is Europe’s largest biomedical research institute under one roof. Our world-class scientists and staff collaborate on vital research to help prevent, diagnose and treat illnesses such as cancer, heart disease, infectious diseases and neurodegenerative conditions. 

The Crick is a place for collaboration, innovation and exploration across many disciplines. A space where the brightest minds can pursue big and bold ideas and discover answers to crucial scientific questions. We support them in a dynamic environment which fosters excellence with state-of-the-art infrastructure, cutting-edge facilities, and a creative and curious culture. We’ve removed traditional boundaries of departments, divisions and disciplines and instead have an open approach that supports every researcher. This gives us the freedom to take risks and carry out high-quality, pioneering research. Creating a space for discovery without boundaries helps us to turn our science into benefits for human health and the economy.

About the role

The Znamenskiy lab studies the relationship between the in vivo function, synaptic organization, and molecular identity of cortical neurons. We aim to understand how connections between different neuronal cell types are organized and how this organization enables the computations they perform. To do this, we combine approaches from systems and molecular neuroscience and develop new tools to relate gene expression and connectivity with the activity of cortical neurons.

The brain contains 100s to 1000s of different types of neurons. To understand how this astonishing cell type diversity supports brain function, we have developed new methods that allow us to measure in vivo functional properties, gene expression profiles and connectivity in the same neurons. Analysing the resulting datasets poses a significant computational challenge.

We are now looking for a Data Scientist/Senior Data Scientist to join the lab.

As a Data Scientist in the lab, you will design, develop, and maintain robust computational pipelines for the analysis and integration of large-scale, multimodal datasets, including spatial transcriptomics, in vivo calcium imaging, and molecular connectomics. Working across several projects, you will enable high-quality, reproducible analysis and help translate complex data into biological insight at the interface of systems and molecular neuroscience.

You will play a central, highly collaborative role within the lab, acting as the primary point of contact for computational support. This includes advising and supporting lab members on data analysis, troubleshooting analytical challenges, and ensuring best practices in scientific coding and workflow development are shared and adopted across projects.

We are seeking a collaborative data scientist with strong experience in scientific programming in Python, and a genuine interest in supporting others while building scalable, well-designed analysis pipelines. This role is ideal for someone with a background in neuroscience or computational data science who wants to remain close to cutting-edge research and unique datasets, without pursuing an independent research track, while making a meaningful and lasting contribution to a dynamic scientific environment.

What you will be doing

Typical activities include:

Key projects and data modalities:Spatial transcriptomics data generated from a custom-built automated in situ sequencing microscopesIn vivo multiphoton calcium imaging dataRegistration and integration of spatial transcriptomics and in vivo imaging data Optimise and maintain data analysis pipelines Refine algorithms for image registration, cell segmentation, source separation etc. Develop quality control metrics for experimental data Document analysis pipelines to make them accessible to users within and outside the Znamenskiy lab Support and train users in applying the analysis pipelines Provide training and support to lab members in coding and data analysis and act as a key point of contact to help lab members troubleshoot computational issues

About you

You will have:

PhD in neuroscience computer science, or related fields, or equivalent experience Expertise in analysis of large-scale datasets, for example sequencing, imaging, physiology or circuit tracing data * Strong coding skills in python and knowledge of data science libraries * Knowledge of software development best practices, including version control and package management * Experience with high performance computing * Track record of writing papers as evidenced by preprints and/or publications in peer-reviewed journals

(*Minimum criteria)

About Working at the Crick

Our values

Everyone who works at the Crick has a valuable role to play in advancing the Crick’s mission and shaping our culture! 

We are bold. We make space for creative, dynamic and imaginative ideas and approaches. We’re not afraid to do things differently.  We are open. We’re highly collaborative and interactive, and make sure our activities are visible to the outside world.  We are collegial. We show respect for one another, work cooperatively and support the wider community. 

At the Francis Crick Institute, we believe that diversity and inclusion are essential to driving innovation and scientific discovery. We are committed to creating a workplace where everyone feels valued, respected, and empowered to succeed, regardless of their background, identity, or personal circumstances. We actively encourage applications from individuals of all genders, ethnicities, abilities, and experiences.

We are a Disability Confident: Committed employer and want to ensure that everyone can apply and be part of our recruitment processes and so we'll make reasonable adjustments if you need them - just let us know when you apply. If you need assistance with applying (i.e., would like to apply by phone or post) please email:

What will you receive?

At the Francis Crick Institute, we value our team members and are proud to offer an extensive range of benefits to support their well-being and development: 

Generous Leave: 28 days of annual leave, plus three additional days over Christmas and bank holidays.  Pension Scheme: Defined contribution pension with employer contributions of up to 16%.  Health & Well-being:  24/7 GP consultation services.  Occupational health services and mental health support programs.  Eye care vouchers and discounted healthcare plans.  Work-Life Balance:  Back-up care for dependents.  Childcare support allowance.  Annual leave purchase options.  Crick Networks offering diverse groups’ support, community and inclusive social events. Perks:  Discounted gym memberships, bike-to-work scheme, and shopping discounts.  Subsidised on-site restaurant and social spaces for team interaction. 

Related Jobs

View all jobs

Machine Learning Engineer Python AWS

Senior Data Scientist

Lead Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.