About the Role
We have an opportunity for either a Post Doctoral Research Associate or Computational Biologist* to join the dynamic lab of Dr Inês Sequeira ( https://www.sequeira.science/ ), who co-leads the Oral and Craniofacial Network within the Human Cell Atlas ( https://www.humancellatlas.org/biological-networks/ ). Embedded in an exciting environment at QMUL, you'll have access to state-of-the-art facilities and the latest computational pipelines for multi-omics analysis. This is a fantastic opportunity to be involved in pioneering research that uses multi-omics data to advance human health, focusing on unlocking the mysteries of complex diseases like Epidermolysis Bullosa. The collaborative atmosphere and cutting-edge technologies available in Dr Sequeira's lab and her network will provide a fertile ground for innovative discoveries.
About You
As a Postdoctoral Research Associate, you will have the opportunity to lead a pioneering project exploring the genetic and molecular underpinnings of Epidermolysis Bullosa (EB), with a focus on developing personalised medicine. This role offers the chance to dive into big data, integrating single-cell RNA sequencing and spatial proteomics using the latest computational methods. You will not only employ cutting-edge multi-omics analysis pipelines but also develop new computational techniques to study cellular communication and investigating new targets for drugs re-purposing.
This role is a fantastic opportunity for someone passionate about leading innovative research and making impactful contributions to the field of computational biology.
You will hold a PhD (or close to completion) in Biology, Biochemistry, Bioinformatics, Computational Biology, with strong experience in analysing large multi-modal datasets and proficiency in Python and R. A solid background in single-cell and spatial transcriptomics is desirable. You should have experience working in interdisciplinary teams, bringing together computational, experimental, and clinical expertise to advance ground-breaking research. This is the ideal role for a researcher who thrives on problem-solving, innovation, and contributing to international collaborations aimed at translating cutting-edge discoveries into clinical applications.
As a Computational Biologist ,you'll be at the forefront of cutting-edge research, leveraging big data to explore new therapeutic targets for personalised medicine in Epidermolysis Bullosa (EB). This role offers an exciting opportunity to work with advanced multi-omics technologies and cutting-edge data integration pipelines.. This is a unique chance to contribute to transformative research in an interdisciplinary, global environment. Your work will focus on developing computational methods to analyse single-cell RNA sequencing and spatial proteomics data, driving discoveries in cellular communication and disease mechanisms
We're looking for an enthusiastic individual with an MSc in Computational Biology, Data Science, who thrives on working with large-scale multi-modal datasets. You should have strong skills in Python and R, with experience in high-throughput data analysis. This role is perfect for someone passionate about pushing the boundaries of personalised medicine through computational biology, with a keen interest in single-cell omics and spatial transcriptomics.
Both roles provide an opportunity to collaborate with peers and international experts Queen Mary University of London, EB House (Austria), King's College London, and the Human Cell Atlas Consortium.
*Progress to the next stage and any subsequent appointment will be made in merit order, not by grade. Whilst the requirements for each post are different and will be assessed as such, there will be consistency in the assessment process, ensuring a single merit list can be produced.
Reasonable adjustments will be made at each stage of the recruitment process. For information on the benefits we offer please visit qmul.ac.uk/human-resources/workqm/benefits/
