PhD Research Intern: Machine Learning for Geospatial Information Systems (GIS) at Microsoft

About the job

• We are seeking a highly motivated PhD intern to join our team for a 6-month internship. The successful candidate will focus on applying artificial intelligence, machine learning, and geographic information systems (GIS) to address critical issues related to sustainability and climate change. This role requires a good understanding of foundation models and diffusion models, to develop innovative solutions that can drive positive environmental impact.

Responsibilities
Key Responsibilities:

• Conduct research in AI, ML, and GIS to develop models and algorithms that address sustainability and climate change challenges.
• Apply foundation models and diffusion models, to analyze and interpret complex environmental data.
• Collaborate with cross-functional teams to integrate AI/ML solutions into existing systems and workflows.
• Develop and maintain data pipelines for processing large datasets.
• Assist in publishing research findings in conferences and journals.
• Stay up-to-date with the latest advancements in AI, ML, GIS, and sustainability research.

Qualifications
Required:

• Currently enrolled in a PhD in Machine Learning, Computer Science, Geospatial analytics, or a related STEM field
• Experience with developing or finetuning foundation and diffusion models.
• Proficiency in programming languages such as Python, R, or Java and deep learning frameworks such as PyTorch, TensorFlow or Jax.
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills, both written and verbal, with the ability to present complex technical concepts to non-technical stakeholders.
• Passionate about building the next generation of Equitable AI technology for Africa and the world

Preferred

• Experience in deploying AI/ML models in production environments.
• Familiarity with cloud computing platforms such as Azure, AWS, or Google Cloud.
• Knowledge of environmental policies and regulations related to sustainability and climate change.
• Publication record in relevant conferences, such as ACL, EMNLP, NeurIPS, ICLR, ICML, etc.