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Temporary-Skilled Trades

North Carolina State University
$15-$20/hr
United States, North Carolina, Raleigh
Jul 18, 2025
Position Information






Posting Number PG195246TM
Position Number N/A
Position Type Temporary
Essential Job Duties
We are seeking a technically skilled and motivated Research Assistant with a strong background in machine learning to join an interdisciplinary initiative focused on modeling plant productivity under varying environmental conditions. This role emphasizes the testing and comparison of predictive algorithms-such as Random Forest and LSTM neural networks-for use in genetic material recommendation systems.
Working as part of Camcore's data science team, the selected candidate will contribute to developing scalable, data-driven strategies for allocating forest genetic material in response to climate variability.
Is Time Limited Yes
If Yes, Appointment Length 6 Months
Wolfpack Perks and Benefits
Department Information


Job City & State Raleigh, NC
Department Camcore
System Information


Classification Title Temporary-Skilled Trades
Working Title Temporary-Skilled Trades
Requirements and Preferences






Work Schedule 8:00 am - 5:00 pm Monday - Friday
Other Work/Responsibilities
Key Responsibilities

  • Design and implement machine learning experiments to predict tree growth and performance using historical trial and environmental data.
  • Benchmark multiple models, including ensemble and deep learning methods, for spatial and temporal accuracy.
  • Develop tools to evaluate model generalizability across sites and climate zones.
  • Collaborate with other researchers to align machine learning outputs with domain-specific insights in forestry.
  • Clean and preprocess large-scale datasets, including climate time series and forest trial measurements.
  • Assist in preparing technical documentation and visualizations for project deliverables.

Minimum Experience/Education
Required Qualifications

  • Master's degree in a relevant field (e.g., Computer Science, Machine Learning, Data Science).
  • Strong coding proficiency in Python (preferred) and/or R, especially with ML libraries such as TensorFlow, PyTorch, XGBoost, or scikit-learn.

Department Required Skills

  • Experience handling structured and time-series data.
  • Familiarity with model validation techniques (e.g., k-fold cross-validation, RMSE, MAE, AUC).
  • Clear communication and documentation skills, especially for interdisciplinary work.

Preferred Years Experience, Skills, Training, Education
Preferred Qualifications

  • Background in ecology, forestry, or environmental modeling is an asset.
  • Experience working with climatic or remote sensing data.
  • Understanding of genotype O environment interaction modeling or phenomics.

Required License or Certification
n/a
Valid NC Driver's License required? No
Commercial Driver's License Required? No
Recruitment Details


Anticipated Hiring Range $15-$20/hr
Recruitment Dates


Job Open Date 07/18/2025
Applicant Information


Quick Link https://jobs.ncsu.edu/postings/220074
EEO
NC State University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, age, sexual orientation, genetic information, status as an individual with a disability, or status as a protected veteran.

If you have general questions about the application process, you may contact Human Resources at (919) 515-2135 or workatncstate@ncsu.edu. Individuals with disabilities requiring disability-related accommodations in the application and interview process, please call 919-515-3148.

Final candidates are subject to criminal & sex offender background checks. Some vacancies also require credit or motor vehicle checks. Degree(s) must be obtained prior to start date in order to meet qualifications and receive credit.

NC State University participates in E-Verify. Federal law requires all employers to verify the identity and employment eligibility of all persons hired to work in the United States.
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