Functional Genomics Intern

Syngenta Group•Durham, NC

2d•Onsite

About The Position

Syngenta's Bioinformatics Team is seeking a Functional Genomics Intern in Durham, NC. This internship role will analyze next-generation genomics 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.

Requirements

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.
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.

Nice To Haves

Experience with high-throughput omics data analysis (e.g., RNA-seq analysis, omics data).
Experience with high-performance computing job schedulers (SLURM, etc.) and cloud computing (AWS, etc.).
Self-motivated, with the ability to work independently and collaboratively.
Enthusiasm for learning new computational methods and tools.
Experience presenting technical work to varied audiences.

Responsibilities

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.