This position focuses on developing and applying AI-driven protein modeling pipelines, including generative and language-model based frameworks (e.g., protein language models, diGusion models), to analyze integrated single-cell RNA-seq and spatial transcriptomics data and predict the functional impact of genomic variation.

Required Skills:
• Master’s degree in Biology, Biotechnology, Bioengineering, Chemistry, Physics, Statistics, or a related scientific discipline.
• Experience with the analysis of next-generation sequencing transcriptomic datasets (bulk RNA-seq, single-cell RNA-seq, or spatial transcriptomics).
• Familiarity with machine learning principles is required.
• Strong interest in biological data interpretation and translating computational insights into biological understanding.

Contract Details:
This is a full-time position with a duration of 2 years. The salary will be commensurate with qualifications and experience.