2024 BNA Scholars announced
15th March 2024
Job details
This job requires the successful candidate to o lead on a range of projects within the group of Dr Albert Cardona at the MRC Laboratory of Molecular Biology (LMB), as part of an overall programme on cellular connectomics, developing and applying software tools for the mapping and analysis of synaptic wiring diagrams from volume electron microscopy and other imaging techniques.
The successful candidate will play a major role in research, introducing new ideas, disseminating research results and delivering the work at seminars and meetings.
They will support and train others, contributing to the strategic development of the group and of the division overall.
Candidates will also have to be a focus of expertise on the usage and development of software tools for cellular connectomics, with particular emphasis on image registration and segmentation and the mapping of synaptic wiring diagrams, using methods from conventional as well as modern machine learning approaches to computer vision and pattern recognition as applied to volume electron microscopy of neural tissue.
The successful candidate will need to manage a budget and collaborations.
Requirements
A PhD or multiple years of research experience in a relevant biological subject, namely neuroscience with a focus on neuroanatomy at the nanometer scale.
Extensive research experience in cellular connectomics, quantitative neuroanatomy, and the reconstruction and analysis of neuronal wiring diagrams from volume electron microscopy with manual and automatic methods.
Experience in the generation of ground truth data for learning machine learning classifiers and graph-theoretic analysis of neural circuits.
Software engineering: adjusting software applications, compiling and running them in computing servers, CPU clusters and GPU clusters. Additionally, knowledge of programming languages, especially Python and the Django framework.
Experience in developing or applying machine learning frameworks for synapse detection and quantification in volume electron microscopy.
Proven experience in interacting with scientists from multiple disciplines and in particular with biologists.
Experience with using machine learning libraries with python bindings such as Keras or PyTorch.
Desirable skills
Application of machine learning approaches to image segmentation in 2D and 3D.
Familiar with microscopy file formats and high-performance image-processing software libraries.
Knowledge of the Rust programming language and Javascript.
Triage of I/O bottlenecks and deployment of optimization approaches, continuously monitoring metrics to ensure consistently optimal computing performance.
Use of machine learning libraries with python bindings such as Keras or PyTorch, with the candidate having written code that uses these libraries and have contributed patches or documentation to these or related machine learning infrastructure projects.
Writing image file format parsers and writers.
Development of APIs for end-user consumption.
PostgreSQL database and knowledge of the SQL programming language.
How to apply
https://mrc.tal.net/vx/appcentre-int/candidate/post/2926/en-GB
Contact details
Dr Albert Cardona: acardona@mrc-lmb.cam.ac.uk.