Research Fellow (Staff Scientist)

Cancer Institute Faculty of Medical Sciences

Job Description

Research Fellow (Staff

Scientist)

Department: Department of Oncology

Reports to

Omer Bayraktar

Context

The UCL Cancer Institute is a world-leading centre for cancer research at University College London, bringing together over 400 scientists and 150 PhD students dedicated to advancing the understanding and treatment of cancer. As part of the CRUK City of London Centre, the Institute collaborates with leading research organisations including Barts, King's College London, and the Francis Crick Institute to drive innovation in cancer research.

We are seeking a highly motivated and skilled Research Fellow (Staff Scietist) to join Bayraktar lab on

2D/3D spatial and single cell transcriptomic analysis of cancer-nervous system interactions.

Professor Omer Bayraktar is a newly appointed group leader at the UCL Cancer Institute and his team explores brain cellular diversity in the health and disease using cell atlassing technologies. The Bayraktar lab is known for developing computational tools for spatial transcriptomics and for creating multiomic atlases of human brain disorders spanning brain cancer, autism and neurodegeneration.

The position is part of a Cancer Grand Challenge Project (Team InteroCANCEption) in Cancer Neuroscience (https://www.cancergrandchallenges.org/interocanception).

Grade: 7

Salary: £43,981-£54,019 per annum

Salaries are inclusive of London Allowance

Location: London An international consortium across 9 labs, this project has the ambitious goal to harness the nervous system to halt tumour progression. To this end, Bayraktar team and collaborators are characterising cancer-nervous system interactions in genetically engineered mouse models and patient tumours using cutting-edge cell atlassing technologies.

Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Research Assistant Grade 6B, with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

Applications should include a CV and a Cover Letter: In the Cover Letter please provide evidence of the essential and desirable criteria in the Person Specification part of the Job Description. (By including a Cover Letter, you can leave blank the 'Why you have applied for this role' field in the application form, which is limited in the number of characters it will allow.) The role is available for 2 years in the first instance with the possibility of extension.

Main purpose of the job

This role will lead spatial transcriptomic technology development and data generation in the Bayraktar lab for Team InteroCANCEption. The role will focus on imaging-based spatial transcriptomics, with dual responsibilities in modifying existing spatial transcriptomics assays towards new neuroscience applications and applying kitted technologies to generate spatial data in cancer neuroscience. The assay development activities will focus on 3D spatial transcriptomics coupled with neuronal tracing and spatial perturbations in complex organoid models. The data generation responsibilities will span the operation and maintenance of a 10X Genomics Atera and a Stellaromics Pyxa platform, coordinating the application of these technologies to nervous system and cancer tissue samples and working with a vibrant team of wet and dry lab biologists across Bayraktar and InteroCANCEption teams. This is a unique opportunity to lead/contribute to publications in cancer neuroscience, apply and further develep with cutting edge spatial omic technologies, and collaborate with world-leading teams in these areas.

Duties and responsibilities

• Perform spatial transcriptomics assay R&D for cancer neuroscience, including 3D spatial transcriptomics coupled with neuronal tracing and spatial perturbation approaches in organoid models.
• Coordinate spatial transcriptomic data generation from cancer and nervous system tissue samples across Bayraktar lab, with a primary focus in cancer neuroscience.
• Day-to-day operation and management of current (i.e. Atera and Pyxa) and future spatial transcriptomics platform in Bayraktar lab. The responsibility will be shared with the CoL Genomics core at the Cancer Institute.
• Independently manage collaborations with wet and dry lab scientists across Bayraktar and InteroCANCeption teams.
• Spatial data and metadata management.
• Strict adherence to sample tracking requirements and SOPs.
• Provide expertise and training to team members on spatial omic assays.
• Facilitate the transfer of samples, consumables and reagents Bayraktar team and collaborators.
• Communicate the results through regular lab meetings, monthly project meetings with collaborators and international scientific meetings.
• To support or lead writing publications.

General

• Follow and actively promote the UCL Ways of Working.
• Takes responsibility to carry out duties in a way that embodies UCL's environmental and social sustainability values, actively supporting UCL's Sustainability Strategy, policies and objectives within the remit of their role.
• Carry out any other duties within the scope, spirit and purpose of the job as requested by the line manager.
• This job description may be reviewed and be subject to amendment in consultation with the post holder.

Person Specification

Note to job applicant: copy and paste the following criteria into your “Statement in support of your application” and describe underneath each criteria how you meet it, giving examples. You will be scored on how you meet each criteria.

Essential Criteria

Qualifications, experience and knowledge

Ph.D. or equivalent experience in a relevant discipline (e.g. Biology, Neuroscience, Developmental Biology, Genetics, Cancer Biology).

Strong background in neuroscience

Strong wet-lab experience in bespoke spatial transcriptomics assays and R&D (e.g.

in situ sequencing, MERFISH, spatial perturbation approaches) Strong wet-lab experience with kitted imaging-based spatial transcriptomics technologies (e.g. Xenium MERSCOPE) Strong background in fluorescent microscopy

Skills and abilities

Experience in tissue handling and preservation for imaging and spatial transcriptomics Experience in cell culture including human/mouse iPSC differentiation and imaging and spatial transcriptomics of cultured cells Basic competency in single cell, spatial or image data analysis in Python programming language Experience with sample and patient metadata trackers Excellence communication skills to allow efficient interactions with collaborators, including regular presentations at weekly and monthly meetings.

Ability to prioritize and organise own work, meet deadlines and manage multiple parallel workstreams.

Ability to interact successfully with others, work collaboratively in a multidisciplinary environment including both experimental and computational team members.

Ability to write up data for reports, manuscripts, presentations and grant-related outputs.

UCL Ways of Working

Innovating and sharing new ways to work efficiently and reproducibly.

Having a positive, helpful and collegial approach to work.

Taking responsibility for your work and contributing to a supportive, inclusive and sustainable research culture.

Desirable Criteria

Strong molecular biology experience

Experience in tissue and organoid culture

Experience in viral work

Familiarity with gene editing