Functional Genomics Intern

At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. We invite you to help shape the future of agriculture and play a role in safely feeding the world while caring for our planet.
At Syngenta, every employee plays a role in safely feeding the world and caring for our planet. Our Bioinformatics group in Durham, North Carolina is seeking a Functional Genomics Intern to analyze next-gen omics datasets and use artificial intelligence prediction tools to solve biological problems. You will develop cutting-edge skills in computational approaches to genomics data analysis and contribute to innovations in agricultural biotechnology. The scope and complexity of the project will be adjusted based on the intern’s experience level and academic background.
As part of Syngenta's Emerging Talent Program, you will gain hands-on experience, exposure to day-to-day business operations, and opportunities to apply your academic knowledge to real-world challenges while developing your professional skills.
Accountabilities:
Gain valuable experience supporting bioinformatics scientists with high-throughput genomics data analysis.
Learn to use cutting-edge AI tools for omics data prediction and analysis.
Work in a multidisciplinary team of computational biologists developing new innovations for agricultural biotechnology.
Contribute to written reports and presentations.
Leverage deep learning models to optimize gene expression in crops.
Document methods, workflows, and code in a reproducible manner.
Create clear visualizations and summaries of analytical results.
Collaborate with team members and communicate findings in group meetings.
Required Qualifications:
Education
Pursuing an MS or PhD in Bioinformatics, Molecular Biology, Genetics, Computer Science, or a related field.
Technical
Expertise with Linux/Unix command-line environments and shell scripting.
Analytical coding languages such as Python or R.
Knowledge of molecular biology and genetics.
Experience using Git for version control.
Vibe coding and use of agentic AI tools.
Analytical
Ability to work with large datasets and implement reproducible computational workflows.
Strong problem-solving skills and attention to detail.
Effective written and verbal communication skills.
Desired Qualifications:
Experience with Deep Learning and DNA LLM .
Experience with high throughput omics data analysis (e.g., RNAseq analysis, Omics data).
Experience with high-performance computing job schedulers (SLURM, etc.) and cloud computing (AWS, etc.).
Self-motivated with ability to work independently and collaboratively.
Enthusiasm for learning new computational methods and tools.
Experience presenting technical work to diverse audiences.

Employment type
Intern

Work arrangement
No