Single cell & spatial bioinformatics scientist
Who are we?
BioLizard is a growing consultancy company providing data science solutions for our customers in biotech and pharma. Typically, a lizard adjusts to its surroundings and that is exactly what we do. At BioLizard we adapt to our customers’ data environment! The research field is rapidly becoming more data-driven, where we strive towards offering state-of-the-art bioinformatics, statistics and machine learning solutions to help solve our customers’ biological questions. Our bioinformaticians are embedded in the working environment of our customers in a full-time or half-time regime, collaborating on challenging projects in life science.
You will engage in developing solutions for data integration, pipeline implementation, machine learning and data visualisation, specifically focusing on spatial and single cell data analysis. You should be adept at experimental design, and computational omics, with a strong passion for analysing single-cell (spatial) data to derive valuable scientific insights for our clients. Experience or interest in spatial technologies and image analysis is also highly desirable. Additionally, you will support internal knowledge transfer for spatial omics and serve as a key liaison to our network of academic specialists, ensuring both professional and personal development.
Keywords
Spatial transcriptomics - Single cell technologies - Analytical mindset – Eager to learn – Independent and team player - Multidisciplinary - Solution-oriented – Positive and open-minded – Customer empathic
Job responsibilities
Conduct spatial omics data analysis, refine bioinformatics tools, and tailor pipelines for single-cell spatial studies starting from exported data from common commercial spatial omics providers (10X, Nanostring, Vizgen) or high-dimensional microscopy images. Work collaboratively with various team members to plan experiments and manage the integration of complex biological data. Keep up-to-date of emerging spatial technologies and methodologies, performing the data analysis within both internal and client-focused projects at a medior to senior level.
Job requirements
Ph.D. preferred in a computational or life sciences field. Alternatively, a Master's degree with at least 3 years of equivalent work experience in single cell bioinformatics or spatial analysis.
- Proven experience with spatial transcriptomics analysis or high-plex spatial proteomics and proficiency in common single cell bioinformatics (such as Scanpy/squidpy, Seurat, Bioconductor, skimage) frameworks is essential. The candidate must be fluent in at least one analysis framework (i.e. R- or python-based) with the flexibility to switch between frameworks based on client requirements.
- Experience applying one or more methods such as advanced cell segmentation and image analysis, analysis of single cell transcriptomics and multi-omic datasets, bulk-single cell data integration or working with single cell atlases is an advantage.
- Familiarity with (applied) machine learning and other omics fields such as bulk genomics, transcriptomics, metabolomics or proteomics is a plus, but not required.
- Knowledge or background in immunology and immuno-oncology is a plus, but not required.
- Fluent in English, with good communication skills
- Currently living in Belgium, the Netherlands, or France.
- Willing to travel or work on-site at the client when the need arises (depending on project)
- Location: preferably Ghent – Belgium, but this is not a must
Job offer
- A challenging and motivating work environment where like-minded people strive towards top-grade results in a continuously evolving research domain
- A personal growth trajectory focusing on self-development and knowledge expansion, guided and mentored by senior profiles
- Genuine attention to your well-being, supported among others by a hybrid work culture and several team activities organised by our own Gecko-team
- An attractive salary package with additional benefits