Postdoctoral Scientist | Neurobiology | Dr Albert Cardona | LMB 2298

To work within the group of Dr Albert Cardona at the MRC Laboratory of Molecular Biology (LMB), within a programme aimed at studying the neural circuit basis of behaviour. Specifically, to map the synaptic wiring diagram, or connectome, of whole brains, using machine learning approaches to computer vision, in a disease animal model. In order to compare the connectome across different experimental conditions, developmental stages, and strains or species, we must first measure the natural variability, by mapping the connectome across multiple individuals and statistically quantifying the individual differences from the common subset.

Mapping the first connectome manually with computer-assisted means took 10 years and the effort of dozens of laboratories. Today, the knowledge acquired, the existence of one mapped connectome to act as reference, the fact that the larval fly brain is composed of stereotyped and uniquely identifiable neurons, plus machine learning approaches to computer vision, offers the opportunity to automatically map many connectomes across many animals, and therefore study how connectomes vary in development, in disease, and across closely related species. Identifying the differences across conditions will help understand the relation between neuronal circuit structure and function.

The candidate will conduct a research project in applying new automated approaches to connectome mapping at scale to many brain volumes of both wild-type and disease models in fruit fly larvae.

• To undertake research aimed at developing new techniques for automated mapping of connectomes from volume electron microscopy.
• To identify, develop and apply a broad range of techniques to pursue the research objectives.
• To present scientific work at seminars within the laboratory and at external meetings.
• To contribute to laboratory-wide discussions on developments within the field.
• To draft scientific papers, and contribute to the overall preparation of research for publication.
• To contribute to the LMB’s mission in the public engagement of science, and the translation of research findings into improvements in health care.
• To assist in the training of PhD students and other members of the LMB.

• Within the overall direction of the programme, the group, the remit of the project and in discussion with the Group Leader, you will make a significant input into determining the direction of the project within a two-year lifespan.
• To plan your own work and objectives on a 12-month basis and manage your experimental work within the project along with your Supervisor.
• To work with limited supervision to identify, develop, modify and apply the necessary techniques to achieve the goals of the project.
• To introduce and apply new techniques across a wide range of disciplines and to have the creativity and initiative to develop novel approaches and methods where required.
• To ensure the research is carried out in accordance with good practice and in compliance with local policies and legal requirements.
• To contribute to the smooth running of the group, including the effective use of resources, training of others and taking responsibility for use of communal facilities.
• To enhance your research and generic skills through a tailored development programme.

You will report to Dr Albert Cardona and will interact and collaborate with other Postdoctoral Scientists, Research Support staff and students, not only in your group, but also across the LMB and with external groups as necessary.

This is a three-year training and development position for a Postdoctoral Scientist who has recently completed their doctoral studies, is moving into a new research discipline or has limited experience of key transferable skills. We support Postdoctoral Scientists with a range of formal and on-the-job training, including: MRC training courses, external training and personal development courses, and one-to-one training with your Supervisor and other Scientists.

• Developing and following a personal development plan.
• Attending training courses.
• Identifying additional training which will support you to develop your career.

These should include a PhD (or due to complete within 6 months) in neuroscience, or in a related field (physics, computer science, applied math, or biology in a quantitative programme within a computational group) where the research project broadly meets the scope of connectomics: bioimage informatics applied to large-scale volumetric densely-labelled data for circuit mapping and analysis, or at least, bioimage informatics applied to neuroscience data such as neuronal activity imaging, neuronal activity monitoring, behavioural tracking, or transcriptomics of neural tissue.

Experience of and ability to perform techniques relevant to the project. The ideal candidate will have a background in neuroscience with expertise in bioimage informatics, with demonstrable experience in computer vision and machine learning applied to image datasets from biology laboratories.

• Experience in neurobiology of Drosophila melanogaster or another laboratory animal model with a powerful genetic toolkit for the manipulation and monitoring of neuronal activity.
• Experience in neuroscience datasets relevant for connectomics.
• Experience in mapping neural circuits.
• Ability to work with version control software.
• Experience in the development and application of machine learning techniques to bioimage informatics for image segmentation and instance reconstruction.
• Experience in managing large datasets using system administrator skills in Linux and *BSD servers, and knowledge of databases such as Postgresql.
• Experience in the use of the Python programming language.
• Knowledge of Fiji and Napari software ecosystems as a user and ideally also as a software developer.

• Ability to write scientific manuscripts.
• Ability to travel internationally and present to scientific conferences.
• Ability to travel internationally for work to visit other laboratories to work in collaboration.

This will include achievements, and contributions to published papers, as well as to open source software published in online version-controlled repositories, and datasets.

• Commitment.
• Originality.
• Ability to communicate.
• Working with others.

Applicants are required to submit a full CV and covering letter.