
Senior Microprotein Analyst
2 weeks ago
About the Role
This is an exciting opportunity to join a pioneering research program at the forefront of proteogenomics and artificial intelligence. Our lab focuses on discovering novel microproteins encoded by the dark proteome, with a particular emphasis on their roles in metabolic disorders and cellular energy metabolism.
We are seeking a talented Computational Biologist to develop innovative computational pipelines integrating ribosome profiling (Ribo-seq), transcriptomics, and metabolomics data. The successful candidate will have expertise in next-generation sequencing data analysis, particularly Ribo-seq, and proficiency in statistical analysis and machine learning methods.
- Develop and implement cutting-edge computational pipelines for the analysis of multi-omics datasets
- Apply and enhance existing smORF identification tools while developing novel AI-driven approaches to predict functionally important microproteins
- Lead the computational analysis of large-scale datasets to prioritize disease-relevant microprotein candidates
Key Responsibilities
The ideal candidate will have a strong publication record in computational biology or related fields, and be able to design prediction models to identify microproteins involved in metabolism, inflammation, and heart disease.
- Collaborate with wet-lab scientists to validate computational predictions and refine prediction models
- Contribute to the development of new algorithms for improved microprotein detection and functional annotation
- Participate in commercialization activities and innovation development
Requirements
To be considered for this role, you must have a Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related field, and possess strong programming skills in Python, R, or similar languages.
- Strong programming skills in Python, R, or similar languages
- Experience with next-generation sequencing data analysis, particularly Ribo-seq
- Proficiency in statistical analysis and machine learning methods
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