S
Research Intern — Geospatial Artificial Intelligence
Remote · دوام جزئى
كن أول من يتقدم بطلب
- خبرة
- أي
- مرتب
- —
- الوظائف الشاغرة
- 1
- تم النشر
- • ٥ نوفمبر
- وضع العمل
- العمل من المنزل
- تعليم
- Postgraduate (GIS, Computer Science, Data Science, or related)
- سيرة ذاتية
- مطلوب للتقديم
المسمى الوظيفي
About the Role
We are inviting applications for a research internship aimed at students or early-stage researchers with an interest in geospatial artificial intelligence. This internship offers a chance to collaborate with our research team on projects centered around spatial data analysis, machine learning, and real-time decision-making systems.
Responsibilities
- Conduct literature reviews and assist in designing experiments for current research projects.
- Develop and assess machine learning models tailored to spatial and temporal datasets.
- Manage and analyze geospatial data using Python programming and GIS software tools.
- Contribute actively to open-source research deliverables and scholarly publications.
- Deliver presentations of research findings during regular team meetings.
Requirements
- Enrollment in or recent completion of a postgraduate degree in Geographic Information Systems, Computer Science, Data Science, or similar disciplines.
- Strong programming skills in Python and familiarity with data science libraries such as NumPy, Pandas, and Scikit-learn.
- Understanding of GIS principles and experience working with geographic information systems.
- Excellent analytical abilities combined with effective communication skills.
- Self-driven with the capability to independently manage research assignments.
Preferred Qualifications
- Prior experience working with deep learning frameworks like PyTorch or TensorFlow.
- Record of published academic work or presentations at conferences.
- Knowledge of remote sensing technologies or spatial database management.
- Proficiency in version control systems such as Git and working in collaborative coding environments.
What We Offer
- Flexible arrangements allowing remote or hybrid work schedules.
- Guidance and mentorship from seasoned research professionals.
- Possibilities to co-author research publications.
- Practical experience in operating production-level geospatial systems.
- A nurturing and intellectually engaging workplace culture.