The KU Leuven Cancer Institute (LKI), the KU Leuven Brain Institute (LBI) , and the KU Leuven Institute for Single Cell Omics (LISCO) have jointly established a state-of-the-art spatial multiomics platform, which is already revolutionizing our understanding of healthy (e.g. development) and diseased tissues (e.g. cancer and neurodegenerative diseases) for future therapy development. The upscaling of integration and analysis of spatial multiomics data now requires a concerted effort, for which we are currently recruiting a dedicated team of data scientists consisting of closely collaborating bioinformaticians, software developers, a data manager, and an AI specialist.
As part of this team, we are recruiting a bioinformatician at Ph.D. level to work on single-cell and spatial multiomics data for neurodegenerative diseases within the KU Leuven Brain Institute and the VIB Center for Brain & Disease Research. Initial projects will focus on the neurodegenerative disorder amyotrophic lateral sclerosis, for which single nuclei sequencing and spatial transcriptomic data will be analyzed to better understand the disease pathways. You will be closely collaborating with the KU Leuven Laboratory of Multi-omic Integrative Bioinformatics and other bioinformaticians working on the spatial multi-omics platform.
To strengthen the spatial biology services in Leuven, we would like to recruit an enthusiastic and energetic computational biologist/engineer/(bio)informatician. In this role, you will be responsible for the bioinformatic analysis of large spatial biology data sets to generate novel biological insights and develop new analysis tools when needed. You will do this in teamwork with the biomedical scientists of our groups.
You will be leveraging and adapting existing spatial data analysis pipelines, and implementing new functionality when needed. The first implementation will be in the context of single-cell spatial transcriptomics with later applications in spatial multi-omics and the required data integration. You will help set up data quality standards, data quality checks, and novel analysis methodology which will be leveraged by the larger internal (LKI, LBI, LISCO) and external academic collaborations, as well as part of the services provided by the spatial core to external clients (e.g. industry). You will also help set up the data analysis and data management infrastructure (both software and hardware) to handle very large-scale datasets. You will serve as a liaison between the different multidisciplinary stakeholders (e.g. computational method developers, biologists, clinicians, lab technicians, industry customers).
We are looking for a (bio)informatician/engineer with an interest in neurobiology who is, well-organized and dynamic with a high level of independence and creative thinking:
- Ph.D. degree in (Bio)informatics / Computational Biology / Computer Science or a related field
- A broad bioinformatics experience in next-generation sequencing technologies and/or spatial biology technologies, and (statistical) data analysis
- Working proficiency in Python and R
- Experienced in handling and managing the analysis of large biological datasets
- Experienced in the development of bioinformatics tools
- Experience in theory and application of deep learning methods and popular DL frameworks (PyTorch, TensorFlow) is a plus.
- Knowledge of computing environments, cloud-based solutions, and hardware specifications to manage data would be advantageous
- Team player who likes to work in a multidisciplinary (international) team
- Excellent oral and written English communication skills
- Organized and respecting deadlines
- Competitive salary and benefits with financial support available for three years (possibly to be extended).
- A stimulating (international, multidisciplinary) environment, where agility, quality, professionalism, and team spirit are encouraged
- The ability to work on scientifically exceptional and high-impact, state-of-the-art projects
- The opportunity to be part of a dynamic team making a meaningful contribution to science
How to apply?
Please complete the online application procedure and include a detailed CV, two reference letters, and a motivation letter.
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