Job Description

Panda Intelligence is pleased to present an exceptional opening for a Computational Biologist with an emerging billion-dollar Biotech scale-up with previous partnerships at two of the top 5 world's largest Big Pharma firms. This is an outstanding opportunity for an ambitious comp biologist to join a pioneering team making significant advances in oncology. The ideal candidate will leverage computational techniques to analyze large-scale genomics datasets, develop predictive models, and contribute to the discovery and development of novel cancer therapies.

Responsibilities:

• Develop and apply machine learning and statistical models to analyze multi-omics datasets (e.g., DNA-seq, RNA-seq, single-cell, proteomics) in oncology research.
• Design and implement computational workflows for biomarker discovery, patient stratification, and therapeutic response prediction.
• Integrate public and proprietary datasets to gain insights into cancer biology and treatment resistance mechanisms.
• Collaborate with wet lab scientists, bioinformaticians, and clinicians to translate computational findings into actionable biological hypotheses.
• Develop and maintain reproducible, scalable, and efficient computational pipelines for data analysis.
• Stay current with emerging trends in AI/ML applications in genomics and oncology and implement best practices.
• Contribute to scientific publications, patents, and presentations at conferences.

Required Qualifications:

• PhD in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or a related field.
• Hands-on experience with genomics and transcriptomics data analysis (e.g., WGS, WES, RNA-seq, scRNA-seq).
• Proficiency in Python, R, or other relevant programming languages for data analysis and ML model development.
• Experience in drug discovery
• Strong knowledge of machine learning techniques (e.g., deep learning, supervised/unsupervised learning, feature selection) and their applications in biological data.
• Experience with cloud computing (AWS, GCP, or Azure) and high-performance computing environments.
• Familiarity with bioinformatics tools and databases (e.g., GATK, Bioconductor, TCGA, COSMIC).
• Strong problem-solving skills and ability to work in a multidisciplinary team.

Preferred Qualifications:

• Experience with multi-modal data integration (genomics, imaging, clinical data).
• Background in network biology, graph-based ML, or NLP for biomedical text mining.
• Experience in precision oncology, or immuno-oncology.
• Knowledge of regulatory considerations in biomarker development and clinical genomics.

If interested, please apply and/or share with your network.

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