A research institute has developed and continues to advance a set of untargeted and targeted spatial, single-cell, single-nucleus, and perturbational omics technologies. These technologies transform the speed, scale and resolution at which in vivo immune-cell pathways can be unravelled.
By combining these approaches with single-nucleus ATAC-seq and spatial data, the aim is to move towards a comprehensive understanding of the regulatory mechanisms that shape liver cell states in health and disease, including metabolism, cancer, regeneration and development.
What you will do.
- Apply innovative computational approaches to analyze a broad range of single-cell and single-nucleus datasets, including RNA-seq, ATAC-seq and perturbational omics.
- Work with spatial transcriptomics data, using technologies such as MERFISH/MERSCOPE, Visium HD and ATERA.
- You can choose to focus more strongly on either single-cell and perturbational data analysis or spatial data analysis, while also gaining exposure to the broader range of technologies.
- Develop, adapt and fine-tune computational pipelines, often building on approaches developed within the lab or institute.
- Work closely with both computational and experimental colleagues to analyze data in a detailed and scientifically sound manner.
- Integrate and compare results across different data types and projects, and uncover biological patterns and insights.
- Strong collaboration and communication across the computational and experimental sides of the lab will be an important part of the role.
What they ask
- Bachelor’s or Master’s degree in bioinformatics, biomedicine, bioengineering, biotechnology or a related field.
- Fluency in written and spoken English.
- Experience in Python and/or R.
- Experience with Linux and Bash.
- Experience with bulk, single-cell or single-nucleus RNA-sequencing data.
- Ability to troubleshoot and resolve data-analysis issues.
- Experience presenting computational results to colleagues from different scientific backgrounds.
Desirable.
- Experience in imaging or spatial omics data analysis.
- Experience with machine learning.
- Basic understanding of immunology.
Profile
- Enthusiastic and curious about scientific research.
- Likes learning new computational techniques and wants to stay at the technological forefront.
- Works accurately and critically assesses analyses and their implementation.
- Works efficiently, is solution- and goal-oriented, and is able to set priorities.
- Flexible and can adapt well to changing priorities.
- Can work well in a team and independently.
- Enjoys other cultures and is respectful of others and their different ideas and opinions.
- A mature and professional team member who communicates openly and respectfully, handles disagreements constructively, and contributes to a positive working environment.
How to apply
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