As a Senior Scientist, you are an important member of a diverse team supporting research in functional genomics, data science and predictive biology to support novel solutions in agriculture. You are passionate about the idea of using bioinformatics, systems biology, and artificial intelligence to find unique solutions to biological problems. You will be involved in the development of biotech products together with diverse talent from multiple functions.
Role Purpose:
Support biotech trait discovery: apply bioinformatics approaches and workflows to analyze data, interpret results, and adjust procedures and methods to achieve research objectives
Apply subject matter expertise to solve various biological problems, become an active member of the Bioinformatics group and drive innovation in a rapidly evolving scientific discipline
Accountabilities:
- Process, analyze and interpret large scale omics datasets, including RNAseq, WGS, GWAS, sc-RNA and chromatin accessibility data from multiple projects
- Develop novel computational approaches to detect gene regulatory patterns in complex biological data and create fundamental datasets for predictive biology
- Collaborate with biologists on lead discovery in multiple crops
- Provide computational skills and subject matter expertise to a range of research projects
- PhD degree in bioinformatics, computational biology, system biology, genetics or related fields; post-doctoral experience preferred
- At least two publications in a mainstream journal in the field of bioinformatics
- Rich experience in bioinformatics analysis, proficient in using R and Python for omics data analysis, data mining and plotting, familiarity with commonly used analysis software and techniques
- Excellent communication skills and the ability to work in multicultural and collaborative teams, enthusiastic about problem-solving
Technical skills
- Experience working with a high-performance computing grid including job scheduling such as Slurm
- Coding in Python and R
- Necessary knowledge to understand biological problems
- Experience with using at least one machine learning/deep learning approach for predictive biology: SVM, Bayesian network, HMM, Random Forest, CNN, encoder/decoder, transformer, etc.
- Preferred but not required:
- Protein structure prediction
- Spatial transcriptomics, sc-RNA seq analysis experience
What We Offer
- A platform with a combination of a booming agricultural industry in China domestic market and global resources and exposure, where you can fully develop your potential
- A culture that promotes Innovation and Entrepreneurial Spirit
- Competitive annual base salary (ABS) and short-term incentive (STI) plans
- Standard social benefits and housing fund package according to Chinese government policies, plus supplementary medical insurance
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