Temporary Machine Learning Research Assistant

PG194360TM

11ASO3279

Temporary

As a “Temp Research Assistant” in the Sozzani Lab, your primary responsibilities will revolve around applying Machine Learning techniques to address key challenges in plant biology and agriculture. You will be tasked with developing and implementing novel algorithms and models to analyze complex biological data sets, such as genomic, physiological, environmental, and agronomic data. Additionally, you will collaborate with interdisciplinary teams to interpret results, generate actionable insights, and contribute to the advancement of plant science research.
This role presents a chance to utilize your proficiency in Machine Learning to make substantial impacts within the domain of plant sciences. The ideal candidate will possess a strong foundation in Machine Learning, data analytics, and computational biology, facilitating the smooth integration of computational methods with domain-specific knowledge. Moreover, proficiency in programming languages and tools such as Python, SQL, R, and MATLAB, will be essential for success in this role. Proficiency with High Performance Computing (HPC), CUDA, and Linux-based servers is a prerequisite.

No

Raleigh,NC

PMB

Temporary-Technical/Paraprofessional

Temporary Machine Learning Research Assistant

25/hrs per week

• n/a

• Relevant Master’s degree or Relevant Bachelor’s and 3 or more years of relevant experience, or relevant independent experience and education

• Proficiency in Machine Learning techniques, including supervised, unsupervised and self-supervised learning, deep learning, and statistical modeling.
• Strong programming skills in Python and R, with experience in data augmentation, visualization, and analysis.
• Familiarity with software tools commonly used in bioinformatics and computational biology (e.g., TensorFlow, PyTorch, scikit-learn).
• Application of data science methodologies across diverse use cases.
• Understanding of plant biology and familiarity with relevant biological data types.
• Ability to collaborate effectively with interdisciplinary teams and communicate complex technical concepts to diverse audiences.
• Demonstrated problem-solving abilities and a track record of delivering high-quality research outcomes.
• Prior experience applying Machine Learning techniques to biological or agricultural data sets.

• Experience with explainable AI (XAI) methods for visualization of deep-learning based neural network models, e.g. LIME and SHAP.
• Strong publication record in relevant peer-reviewed journals and conferences.
• Experience with cloud computing platforms and distributed computing frameworks for scalable data analysis.

• n/a

No

No

$20/hr

05/09/2024

https://jobs.ncsu.edu/postings/201461

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