Graduate Research Assistant – Computer Vision & ML

Penn State; Pennsylvania; Híbrido; USD 25.000 - 28.000; A tiempo parcial

Descripción de la vacante

Penn State College of IST is hiring a part-time, wage payroll Graduate Assistant to contribute to an NSF-funded interdisciplinary project on self-supervised visual learning inspired by human perception. You will work with faculty PIs and students in a collaborative environment.

Responsibilities include developing ML/CV algorithms, testing research software, processing datasets, running experiments, reviewing literature, and assisting with manuscripts and reports.

Formación

• Current enrollment in a graduate program at Penn State (M.S. or Ph.D.).
• Background in artificial intelligence, computer vision, machine learning, or a closely related field.
• Strong programming skills in Python.
• Experience with PyTorch, TensorFlow, or similar deep learning frameworks is preferred.
• Familiarity with computer vision, deep learning, or statistical learning methods.
• Experience with scientific programming, data analysis, or software development in a Linux environment.
• Strong analytical, problem-solving, and communication skills.
• Ability to work both independently and collaboratively within an interdisciplinary research team.
• Excellent organizational skills and attention to detail.

Responsabilidades

• developing and evaluating machine learning and computer vision algorithms
• implementing and testing research software
• preparing and processing image and video datasets
• conducting experiments and statistical analyses
• reviewing relevant scientific literature
• assisting with studies as needed
• documenting research findings
• supporting the preparation of manuscripts, presentations, and research reports

Conocimientos

Python

PyTorch

TensorFlow

Linux

Educación

Graduate student (M.S./Ph.D.)

Herramientas

Python

PyTorch

TensorFlow

Linux

Descripción del empleo

Penn State College of IST is hiring a part-time, wage payroll Graduate Assistant to contribute to an NSF-funded interdisciplinary project on self-supervised visual learning inspired by human perception. You will work with faculty PIs and students in a collaborative environment.

Responsibilities include developing ML/CV algorithms, testing research software, processing datasets, running experiments, reviewing literature, and assisting with manuscripts and reports.