Postdoctoral Scientist

at  MRC Laboratory of Molecular Biology

Cambridge, England, United Kingdom -

Start DateExpiry DateSalaryPosted OnExperienceSkillsTelecommuteSponsor Visa
Immediate08 Oct, 2024GBP 39375 Annual10 Jul, 2024N/AMachine Learning,Algorithms,Informatics,Software,C++,Computer Vision,Collaboration,Sql,Linux,Transferable Skills,Databases,Servers,Learning Techniques,Image Segmentation,Javascript,Rust,Addition,Java,Computer Science,Postgresql,Programming LanguagesNoNo
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Description:

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 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 devising new automated approaches to connectome mapping and to apply these methods at scale to dozens or hundreds of brain volumes.

ACADEMIC QUALIFICATIONS:

These should include a PhD in a relevant subject or due to complete PhD within 6 months.

TECHNICAL SKILLS AND EXPERTISE:

Experience of and ability to perform techniques relevant to the project. The ideal candidate will have a background in bioimage informatics, with demonstrable experience in computer vision and machine learning applied to image datasets from biology laboratories, with a PhD in computer science or a related field. In addition, the candidate will arrive with some experience developing novel algorithms and having published them in scientific journals or computer science conferences. Experience in using modern machine learning libraries such as PyTorch and their execution in GPUs, plus experience in several other programming languages, ideally Rust, Java, or C++, and JavaScript, would be desirable. In particular, we seek a candidate with experience in developing new machine learning approaches to object boundary segmentation, in instance segmentation, and in quantitative methods for monitoring and improving the performance of software. Furthermore, the ideal candidate will be able to comfortably demonstrate and or learn, either Linux or *BSD operating systems, performing system administration tasks on servers, and executing software in GPU and CPU clusters for high-performance computing.

In particular:

  • Ability to work with version control systems.
  • 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.
  • Experience in the use of GPU and CPU computer clusters.
  • Experience in implementing algorithms into version-controlled software packages for use by others.
  • Ability to write scientific manuscripts.
  • Ability to travel and to present to scientific conferences.
  • Ability to travel for work to visit other laboratories to work in collaboration.
  • Knowledge of Fiji and Napari software ecosystems as a user and as a software developer.
  • Knowledge of other programming languages including Rust, Java, C++, SQL and JavaScript.

ADDITIONAL INFORMATION:

Ability to travel internationally to scientific conferences and for extended visits to other laboratories.
Further Information

You must at all times carry out your responsibilities with due regard to the UKRI:

  • Code of Conduct
  • Equality, Diversity and Inclusion policy
  • Health and Safety policy
  • Data Protection policy

Job descriptions should be reviewed on a regular basis and at the annual appraisal. Any changes should be made and agreed between you and your manager.
The above lists are not exhaustive, and you are required to undertake such duties as may reasonably be requested within the scope of the post. All employees are required to act professionally, co-operatively and flexibly in line with the requirements of the post, the MRC and UKRI.
The role holder will be required to have the appropriate level of security screening/vetting required for the role. UKRI reserves the right to run or re-run security clearance as required during the course of employment.
The MRC is a great place to work and progress your career, be it in scientific research or the support functions.The MRC is a unique working environment where our researchers are rewarded by world class innovation and collaboration opportunities that the MRC name brings. The MRC is an excellent place to develop yourself further and a range of training & development opportunities will be available to you, including professional registration with the Science Council.
Choosing to come to work at the MRC (part of UKRI) means that you will have access to a whole host of benefits from a defined benefit pension scheme and excellent holiday entitlement to access to employee shopping/travel discounts and salary sacrifice cycle to work scheme, as well as the chance to put the MRC and UKRI on your CV in the future.

Responsibilities:

MAIN DUTIES:

  • 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.

KEY RESPONSIBILITIES:

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 three-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 must at all times carry out your responsibilities with due regard to the UKRI:

  • Code of Conduct
  • Equality, Diversity and Inclusion policy
  • Health and Safety policy
  • Data Protection polic


REQUIREMENT SUMMARY

Min:N/AMax:5.0 year(s)

Information Technology/IT

IT Software - Application Programming / Maintenance

Software Engineering

Phd

Proficient

1

Cambridge, United Kingdom