Responsibilities

• 1. Utilize state-of-the-art data mining technologies to process, analyze and interpret multi-omics data, including genomics, transcriptomics, proteomics, and metabolomics. 

• 2. Design and develop sophisticated computational models to assist in analyzing complex biological datasets. 

• 3. Apply statistical and machine learning methodologies to extract meaningful insights from complex biological datasets. 

• 4. Employ cutting-edge network analysis approaches to identify key biological pathways, regulatory interactions, and functional modules within biological systems to uncover potential targets for pathway and metabolic engineering. 

• 5. Integrate diverse biological data sets to gain a comprehensive understanding of cellular behavior and system-level responses for experimental design and guide decision-making processes. 

• 6. Effectively communicate complex analysis results and scientific findings. 

• 7. Collaborate with cross-functional teams to address complex biological questions and develop innovative solutions to biomanufacturing challenges. 

• 8. Keep up-to-date with the advancements in the field and apply emerging technologies to advance projects. 

• 9. Participate with IP team to protect, enrich and increase value of the company's technology IP portfolio.  

Qualifications 

• 1. Engineer or Ph.D. degree in Bioinformatics, Computational Biology, Computer Science, or related fields. Preferably with 3 years of experience working in metabolic engineering in industrial settings or a similar environment. MSc with significant relevant experience will be considered. 

• 2. Excellent background in hands-on analyzing high-throughputbiomedical data: data cleaning, functional annotation, normalization, analysis, interpretation and visualization.  

• 3. Experience in genomic data mining and identifying functions of potential genes via bioinformatics and/or artificial intelligence/machine learning approaches are essential. 

• 4. Extensive development experience with R, JAVA, C, C++, or Python languages. 

• 5. Strong statistics and mathematics background, experience with AI or machine learning is a plus. 

• 6. Must be safety-oriented, self-motivated, and highly organized individuals.  

• 7. Capable of adapting and working well in a collaborative, fast-paced work setting, contributing to a positive and inclusive team culture. 

• 8. Demonstrates excellent verbal and written communication skills in Chinese, preferably in English as well. 

• 9. Strong interpersonal skills, with the ability to effectively communicate and collaborate with colleagues.