Senior Computational Biologist

Senior Computational Biologist

Department: Data Science, PIRC
Reports to: Director of AI in Drug Development

We are seeking a highly motivated and skilled Senior Computational Biologist to join our dynamic data science team. This individual will apply advanced OMICS-oriented analytical methods, statistical modeling, and ML/AI to accelerate discovery and decision-making in support of PIRC’s expanding research programs. The ideal candidate will leverage their deep expertise in computational biology, deep learning, and data-driven drug discovery to develop state‑of‑art solutions.

This role involves close, cross‑functional collaboration with Immunology, Translational Science, and Biologics teams to build sophisticated algorithms and predictive models that drive our pipeline.

It’s not often you get the chance to make a real impact on the lives of others, while expanding your own possibilities. You’ll find that rare opportunity n us, and let’s transform lives, together. Pharma Essentia Corporation is a rapidly growing biopharmaceutical innovator. We are leveraging deep expertise and proven scientific principles to deliver effective new biologics for challenging diseases in the areas of hematology and oncology, with one approved product and a diversifying pipeline.

We believe in the potential to improve both health and quality of life for patients with limited options today through the combination of rigorous research and innovative thinking. Founded in 2003 by a team of Taiwanese‑American executives and renowned scientists from U.S. biotechnology and pharmaceutical companies, today we are listed on the Taipei Exchange (TPEx: 6446) and are expanding our global presence with operations in the U.S., Japan, China and Korea, along with a world‑class biologics production facility in Taichung.

This role will be in the Pharma Essentia Innovation Research Center (PIRC), the US R&D center for Pharma Essentia. As PIRC is essentially in startup mode with the full backing of Pharma Essentia HQ, this is an exciting time for PIRC and the Data Scientist will have great influence in developing and growing PIRC from the ground floor up.

• Lead multi‑omics data analysis across diverse datasets, including genomics, bulk and single‑cell transcriptomics, proteomics, metabolomics and pathway analysis, to address critical questions in target identification, prioritization, and translational science
• Design and implement novel computational modules and frameworks to enable seamless integration and interpretation of multi‑omics data, driving insights for R&D
• Develop and apply machine learning and AI algorithms to uncover patterns and generate predictions from complex biological datasets, and accelerate target discovery and validation efforts
• Enhance internal cross‑disciplinary collaboration with project teams to align computational strategies with project goals and ensure robust biological interpretation of data
• Establish best practices for data management, quality control, and reproducibility in bioinformatics pipelines, and create intuitive visualizations and detail‑oriented reports to communicate findings with stakeholders, enabling data‑driven decision‑making
• Continuously evaluate and adopt cutting‑edge computational tools, algorithms and technologies to stay at the forefront of the field and enhance data analysis capabilities
• Contribute to the strategic planning of computational/AI initiatives, influencing the direction of research programs and technological investments
• Contribute to scientific publications, conference presentations, showcasing advancements in bioinformatics and AI, and their impact on drug discovery and translational research

• Ph.D. in Bioinformatics, Computational Biology, Computer Science or relevant quantitative discipline
• At least 3‑years work experience in combining bioinformatics/computational biology analysis and cutting‑edge computational approaches (including ML/AI) for project support in cross‑functional biotech or pharma setting.
• Expertise in multi‑omics data analysis and result interpretation (genomics, transcriptomics and scRNASeq are must,…