Senior Computational Biologist - Genomics

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 worlds 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.**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 *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 ****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.

Created: 2025-02-20