1. Oligonucleotide drug design

Responsible for design of small nucleic acid drugs (e.g., siRNA, ASO). Use bioinformatics tools and algorithms to analyze gene expression profiles, variations, and splicing isoforms in biological samples for target selection. Apply machine learning platforms for oligo sequence design. Read and run Python, R, and Bash scripts. Optimize and improve existing design algorithms. Create new design workflows and platforms including design of chemical modifications for oligo drugs. Actively participate in project discussions and reports.

1. Off-target analysis

Understand and apply principles and algorithms for off-target evaluation. Analyze and interpret high-throughput next-generation sequencing data, including data preprocessing, quality control, alignment analysis, differential expression analysis, and full pathway analysis. Adjust sequence alignment program parameters to meet the needs of short sequence matching.

1. Data mining and database construction

Use bioinformatics resources from public databases (like NCBI, Ensembl, UniProt, etc.) and combine with the company's internal data to build knowledge bases and databases to accelerate oligo drug discovery.

1. Cross-department collaboration

Work closely with wet lab drug discovery team including in vitro and in vivo teams, chemistry team, etc., participate in project discussions, support bioinformatics aspects of the projects. Analyze results and obtain insights to improve the bioinformatics models and workflows.

• PhD in bioinformatics, computational biology, molecular biology, genetics, computer science, CADD, or related fields.
• More than 5 years of experience in bioinformatics analysis or project experience in small nucleic acid drug development.
• Good communication skills and team spirit, able to collaborate effectively with team members from different backgrounds.
• Strong learning and problem-solving abilities, able to quickly grasp new knowledge and technologies.
• Strong interest in drug development, able to handle work pressure.
• Good English writing and communication skills, able to use both English and Chinese as working languages.
• Familiar with bioinformatics databases (like NCBI, Ensembl, UniProt, etc.) and data mining methods.
• Proficient in bioinformatics analysis tools and software, such as BLAST, Bowtie, SAMtools, DESeq2, Cufflinks, STAR, etc., capable of independently analyzing high-throughput sequencing data.
• Strong programming skills, proficient in Python or R, able to develop and optimize bioinformatics analysis pipelines. Familiar with Linux systems.
• Good coding habits, understands version control and how to avoid errors

Additional preferred qualifications:

• Able to apply machine learning and AI in bioinformatics, with relevant project experience preferred.
• Ability to use cloud computing for bioinformatics analysis.
• CADD-related software and skills, such as RDkit, Schrodinger, etc.
• Experience and skills in multi-omics analysis.
• Additional programming skills like Perl, C, etc.