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Connectomics Data Analysis Engineer (Neuroscience/computer vision)
| Posting date: | 18 March 2025 |
|---|---|
| Salary: | £50,000 per year |
| Hours: | Full time |
| Closing date: | 17 April 2025 |
| Location: | London, UK |
| Remote working: | On-site only |
| Company: | The Francis Crick Institute |
| Job type: | Contract |
| Job reference: |
Summary
Connectomics Data Analysis Engineer (Neuroscience/computer vision)
This is a full-time, fixed term three 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.
About the role…
We are looking for a motivated research scientists to work at the cutting-edge intersection of neuroscience and machine learning. The main goal is to develop computational pipelines primarily for volume electron microscopy-based connectomics to elucidate the synaptic wiring of entire insect brains and portions of mammalian brains.
The position will focus on major connectome projects across three groups: Andreas Schaefer, Lucia Prieto-Godino, and Michael Winding. You will be fully integrated into the science of the connectomics field. You will be expected to keep up with and test the latest computational methods, develop their own new methods, contribute to and/or produce independent publications, and present findings at seminars and key conferences.
The Connectomics Data Analysis Engineer will become an established and well-known figure in the connectomics field, acting as a representative of the three groups and the Francis Crick Institute.
This is a highly collaborative position. You will be embedded in the Software Engineering and AI team at the Francis Crick Institute, as well as communicating closely with the Electron Microscopy team. You will be fully immersed in the science of the Schaefer, Prieto-Godino, and Winding groups.
What you will be doing…
As a Connectomics Data Analysis Engineer at the Crick, you will:
Stay current with the latest thinking in the connectomics field through building a library of related publications
Disseminating work through publications in neuroscience and related journals and through presentation at major connectomics conferences
To develop machine learning based analyses approaches for segmentation and analysis of connectomics datasets as described above
Develop approaches to evaluate the performance of ML models for neuron segmentation, synapse identification etc.
Design and develop high-quality, optimised and maintainable pipelines and software to meet the requirements of the connectomics community
Work in close collaboration with laboratory scientists and other project team members to understand the full range of data and meta-data being produced for the project
Assist with creating and supporting a productive and efficient standardised model development work-flow as appropriate for the project (including versioning and automation)
About you…
You will bring…
Background in the field of connectomics
Strong mathematical/statistical background with demonstrable experience in developing machine learning algorithms (including deep learning) for computer vision projects
Expert level technical programming skills, with emphasis on Python (NumPy, PyTorch etc)
Experience working with large-scale electron microscopy volumes at high resolution, or equivalent high-dimensional, large-scale bioimaging datasets
Ability to read machine learning research articles and quickly/iteratively implement and test the algorithms described
Experience of working with high performance computing clusters
An understanding of good software engineering principles
An understanding of reproducibility, repeatability and replicability for scientific software
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 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:
weronika.kucala@crick.ac.uk
Find out what benefits the Crick has to offer:
For more information on our great pay and benefits package please click here: https://www.crick.ac.uk/careers-and-study/life-at-the-crick/pay-and-benefits
This is a full-time, fixed term three 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.
About the role…
We are looking for a motivated research scientists to work at the cutting-edge intersection of neuroscience and machine learning. The main goal is to develop computational pipelines primarily for volume electron microscopy-based connectomics to elucidate the synaptic wiring of entire insect brains and portions of mammalian brains.
The position will focus on major connectome projects across three groups: Andreas Schaefer, Lucia Prieto-Godino, and Michael Winding. You will be fully integrated into the science of the connectomics field. You will be expected to keep up with and test the latest computational methods, develop their own new methods, contribute to and/or produce independent publications, and present findings at seminars and key conferences.
The Connectomics Data Analysis Engineer will become an established and well-known figure in the connectomics field, acting as a representative of the three groups and the Francis Crick Institute.
This is a highly collaborative position. You will be embedded in the Software Engineering and AI team at the Francis Crick Institute, as well as communicating closely with the Electron Microscopy team. You will be fully immersed in the science of the Schaefer, Prieto-Godino, and Winding groups.
What you will be doing…
As a Connectomics Data Analysis Engineer at the Crick, you will:
Stay current with the latest thinking in the connectomics field through building a library of related publications
Disseminating work through publications in neuroscience and related journals and through presentation at major connectomics conferences
To develop machine learning based analyses approaches for segmentation and analysis of connectomics datasets as described above
Develop approaches to evaluate the performance of ML models for neuron segmentation, synapse identification etc.
Design and develop high-quality, optimised and maintainable pipelines and software to meet the requirements of the connectomics community
Work in close collaboration with laboratory scientists and other project team members to understand the full range of data and meta-data being produced for the project
Assist with creating and supporting a productive and efficient standardised model development work-flow as appropriate for the project (including versioning and automation)
About you…
You will bring…
Background in the field of connectomics
Strong mathematical/statistical background with demonstrable experience in developing machine learning algorithms (including deep learning) for computer vision projects
Expert level technical programming skills, with emphasis on Python (NumPy, PyTorch etc)
Experience working with large-scale electron microscopy volumes at high resolution, or equivalent high-dimensional, large-scale bioimaging datasets
Ability to read machine learning research articles and quickly/iteratively implement and test the algorithms described
Experience of working with high performance computing clusters
An understanding of good software engineering principles
An understanding of reproducibility, repeatability and replicability for scientific software
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 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:
weronika.kucala@crick.ac.uk
Find out what benefits the Crick has to offer:
For more information on our great pay and benefits package please click here: https://www.crick.ac.uk/careers-and-study/life-at-the-crick/pay-and-benefits