Postdoctoral Researcher

Core Requirements

• Awarded a PhD within the previous 5 years, or an MD or DDS within the previous 10 years in a relevant quantitative or biomedical discipline, including but not limited to: Computational Biology, Bioinformatics, Systems Biology, or Quantitative Genomics, Biostatistics,  Data Science, Biomedical Engineering, or related fields.
• Demonstrated experience developing or applying computational or statistical pipelines to molecular, biological, clinical, or multi-omics data.
• Strong foundation in statistical and computational modeling and data analysis is required; experience with machine learning methods is considered an asset.
• Strong programming skills in Python and/or R, with experience in scientific computing and data analysis libraries (e.g., pandas, NumPy, SciPy, Bioconductor, scikit-learn).
• Experience working with large-scale biomedical datasets, such as multi-omics data, clinical genomics, electronic health record-derived data, or treatment-response datasets.
• Proficiency with reproducible workflow management systems such as Snakemake, Nextflow, or equivalent pipeline frameworks.
• Familiarity with cloud or high-performance computing environments, such as GCP, AWS, SLURM-based clusters, or equivalent infrastructure.
• Understanding of data harmonization, privacy-preserving analysis, secure distributed computing, or clinical data governance is highly desirable.
• Strong publication record, commensurate with career stage, in computational biology, bioinformatics, biostatistics, biomedical data science, or related fields.
• Excellent communication skills and ability to work collaboratively in interdisciplinary teams spanning computational biology, machine learning, software engineering, oncology, and clinical research.