Bioinformatics-R shiny

Excelra

R-Shiny Bioinformatician

Location

Europe

Hybrid

Excelra is a leader in biopharma data and analytics, that uniquely blends scientific understanding with technological expertise. This dual mastery empowers innovative drug discovery and development, transforming research data into actionable insights for groundbreaking discovery.
We have locations in Hyderabad (head offices – India), Ghent (Belgium), London (UK), Utrecht (The Netherlands), and Boston/SFO (US).
Website:

www.excelra.com

We are hiring a R-Shiny Bioinformatician to develop, maintain, and enhance scientific applications and bioinformatics solutions that support research programs across multiple therapeutic and scientific domains.
This role combines bioinformatics, scientific software development, cloud technologies, data visualization, and AI-enabled analytics. You will work across a broad range of omics datasets including transcriptomics, genomics, proteomics, microbiome, and single-cell sequencing data while developing interactive applications that empower scientists to explore and interpret complex research data.
You will play a key role in delivering analytical solutions, building scalable data products, and supporting cloud-based platforms that enable researchers to generate insights from diverse biological datasets.

Key Responsibilities

Develop, maintain, and enhance R Shiny applications for exploration, visualization, and interpretation of omics and clinical datasets.
Build interactive dashboards and analytical tools that enable researchers to generate publication-ready figures and insights.
Work closely with scientific stakeholders to translate research requirements into practical application features.
Maintain and improve existing scientific software platforms and analytical applications.

Deliver bioinformatics analyses and software solutions across multiple research programs covering transcriptomics, genomics, proteomics, and microbiome data.
Conduct RNA-seq, single-cell RNA-seq, genomics, microbiome, and multi-omics analyses.
Support interpretation of complex biological datasets and communicate findings to multidisciplinary teams.
Contribute to the development and execution of reproducible analytical workflows.

Design and develop tools that support scientific data exploration, analysis, and reporting.
Develop automated workflows and analytical pipelines for processing biological datasets.
Build and maintain solutions that improve researcher productivity and reduce manual analytical effort.
Support data integration and harmonisation across multiple biological data sources.

Build and maintain AWS-hosted analytical platforms and applications.
Support cloud infrastructure components including data storage, application hosting, monitoring, security, and user access management.
Develop and maintain deployment pipelines for scientific applications.
Integrate AI-powered capabilities into analytical platforms to improve scientific discovery and data accessibility.

Collaborate with scientists, bioinformaticians, software engineers, and project stakeholders across multiple client and internal projects.
Present analytical findings and technical solutions to both technical and non-technical audiences.
Contribute to best practices in software development, documentation, testing, and reproducible research.
Support continuous improvement of scientific data platforms, workflows, and analytical methodologies.

A PhD in Bioscience engineering, Bioinformatics, computer science, Computational Biology, Data Science, Computer Science, Genomics, Systems Biology, or a related discipline– or an MSc with 5+ years of equivalent experience. You can demonstrate this through peer-reviewed publications, contributions to public code repositories, or relevant project work.
Strong experience with R and R Shiny application development.
Experience working with transcriptomics, genomics, proteomics, microbiome, or other omics datasets.
Experience conducting RNA-seq and/or single-cell sequencing analyses.
Strong programming skills in R and Python.
Experience building scientific software applications and data visualization solutions.
Experience working with AWS cloud services and cloud-hosted analytical applications.
Experience developing reproducible analytical workflows and bioinformatics pipelines.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and collaboration skills.
Ability to work independently while partnering effectively with multidisciplinary teams.

Experience with single-cell RNA-seq analysis and multi-omics integration.
Experience developing interactive scientific dashboards and data products.
Experience building applications using AWS services such as S3, ECS, CloudWatch, Cognito, and WAF.
Experience integrating AI assistants, LLMs, or generative AI capabilities into scientific applications.
Experience with microbiome data analysis including WGS and 16S datasets.
Experience with proteomics and translational research datasets.
Experience developing literature mining, knowledge extraction, or scientific text-mining tools.
Experience with Docker and containerised deployments.
Experience with Git, CI/CD, and software development best practices.
Experience supporting pharmaceutical, biotechnology, CRO, or life sciences research environments.

A challenging job environment with advancement opportunities.
Flexible hybrid working in an international setting.
A dynamic company with an open culture, easy communication, and an ambitious vision.
A rich and global team with a mix of backgrounds, experiences, and expertise.
Independence and flexibility.
Opportunities to work across diverse research programs spanning genomics, transcriptomics, microbiome, proteomics, cloud technologies, and AI-enabled scientific applications.
An attractive salary package with extra-legal benefits.