Postdoctoral Researcher
Core
Develop computational methods to study cellular diversity and cancer evolution in response to anti-cancer therapies using multi-omic and single-cell data.
Role type
Postdoctoral Researcher (Computational Biology/ML)
Builds
Novel multi-omic integration methods, deep-learning architectures for tracking cancer evolution, and reproducible high-throughput analysis pipelines.
Domain
Oncology / Computational Biology / Single-cell Genomics
Deliverable
production ML models | research
Required skills
Python, Linux, statistics, machine learning, deep learning, version control (Git/GitHub), data analysis pipelines
Preferred skills
Next generation sequencing data formats (FASTQ, BAM, HDF5), Haskell, R, LaTeX
Technologies
Python, Linux, Git, GitHub, FASTQ, BAM, Matrix Market, HDF5
Responsibilities
Develop novel computational methods to identify cellular populations using multiomic integration; Track cancer-cell evolution across treatments using deep-learning architectures; Identify biomarkers associated with different anti-cancer treatments; Determine tumor microenvironmental factors associated with disease progression and treatment resistance; Disseminate research through national / international conferences and high-impact publications; Develop reproducible pipelines for high-throughput data analysis
Seniority
Postdoctoral (1-3 years post-PhD)