(Associate) scientist translation research Single-cell omics & AI
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Monthly Salary:
Posted on:
3 hours ago
Vacancies:
1 Vacancy
Job Summary
Duration: 1-year fulltime contract l Location: hybrid (Ghent Leuven)
Key words: Single-cell omics AI Virtual Cell Gene Regulatory Networks Valorization
About us
This role sits within VIB Innovation & Business AI Studio a growing team that turns VIBs biological data and AI expertise into trustworthy reproducible digital assets that accelerate innovation in healthcare and biotechnology through validation engineering and valorization pathways such as licensing partnerships and spinouts.
About the role
We are seeking a Computational Biology Scientist in Single-cell omics & AI to support the valorization trajectory of a computational platform combining singlecell omics AI machine learning and translational biology. The role involves collaboration with academic research group(s) with a strong focus on bridging advanced computational methods to biologically meaningful outcomes. The successful candidate will contribute to the application evaluation and interpretation of AI models on single-cell biological datasets while keeping downstream translation and valorization potential in clear focus.
Key responsibilities
- Apply and evaluate advanced machinelearning approaches on singlecell and gene regulatory data to extract biologically relevant signals and propose meaningful and testable hypotheses grounded in disease biology.
- Perform endtoend processing quality control integration and analysis of singlecell and multimodal omics datasets (e.g. scRNAseq scATACseq).
- Train evaluate and benchmark deep learning models operating on singlecell regulatory or multimodal biological data.
- Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources.
- Work closely with academic partner groups and the Innovation & Business (I&B) team to align technical development with biological relevance and translational objectives.
- Contribute to discussions on valorization pathways including positioning of results for partnerships licensing or venture creation.
Your profile
- PhD (or equivalent experience) in Computational Biology Bioinformatics Systems Biology Machine Learning or a related field.
- Strong handson experience with singlecell omics analysis particularly scRNAseq and/or scATACseq.
- Practical experience applying machine learning or deep learning methods to biological data.
- Proficient in Python with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM).
- A pragmatic scientist who combines technical depth with a clear translational goaloriented mindset.
- Ability to critically interpret computational and bioinformatics outputs in a biological and diseaserelevant context.
- Curious proactive and motivated to operate at the interface of research innovation and valorization.
Desirable / Plus
- Hands-on experience with deep learning frameworks (e.g. PyTorch TensorFlow) in a research context.
- Industry experience in pharma and/or biotech particularly in translational research datadriven discovery or applied computational biology.
- Knowledge of DevOps practices software testing or reproducible workflow development.
Our offer
- A 1-year fulltime position with a flexible hybrid onsite/remote working model combining time at VIB headquarters in Ghent and academic groups at VIBs Research Centers.
- A unique opportunity to help shape a cuttingedge AIdriven biology platform with direct exposure to realworld translational and valorization activities.
- A comprehensive social security package including pension scheme and health care coverage.
- Strong support for lifelong learning with access to VIBs personal and professional development programs.
How to apply
Motivated candidates can apply via the online VIB application form ( The application (in English) should consist of:
- Cover/motivation letter
- CV
More info:
Key Skills
- Laboratory Experience
- Machine Learning
- Python
- AI
- Bioinformatics
- C/C++
- R
- Biochemistry
- Research Experience
- Natural Language Processing
- Deep Learning
- Molecular Biology
