IBM Research Brasil is hiring research scientists to join the Spatiotemporal Machine Learning group, which conducts research in machine learning techniques for spatiotemporal data, with the objective of accelerating scientific discovery in climate & sustainability.
More specifically, we work on advanced artificial intelligence and statistical techniques for modeling environmental and climatic phenomena using large geospatial databases.
We are interested both in predictive models, capable of explicitly modeling spatiotemporal series as well as generative models that can be trained for the generation of new realistic scenarios or for increasing the resolution of existing data.
We also develop machine learning techniques that incorporate physical information about the phenomena being modeled and whose results can be interpreted physically.
Deep Learning, Predictive Modeling, Geospatial Data Analysis, Generative Models, Physics-Informed Machine Learning, Artificial Intelligence for Physical Simulations.
In this role, you will join a strong and motivated team to advance fundamental science, develop groundbreaking technologies and publish in top-tier journal and conferences, while helping to shape new product offers in technical and scientific areas.
You will be working in a stimulating environment, leveraging cross-disciplinary expertise in science and technology to transform the scientific discovery practice.
You will participate in high-value projects in collaboration with otherIBM Research Labs and Business Units, as well as with industry and academic partners.
Required Technical and Professional Expertise
Excellent Command of the English language (both verbally and in writing)
Demonstrated ability to tackle complex problems derived from real-world use cases and design, build, and validate effective solutions.
Eagerness to pursue applied research.
Proven ability to work successfully across multi-disciplinary world-wide teams to tackle complex scientific and technical challenges.
Ability to communicate the outcome and impact of your work, internally and externally, e.g., through demos, open-source community engagement, participation in industry conference and workgroups, or publications in conferences and journals.
Teamwork, initiative, self-motivation, creativity, and willingness to learn.
A PhD in Computer Science, Informatics, Engineering, Information Systems, Applied Mathematics, or a related discipline.
Expertise in at least one of the following areas:
Deep Learning, Predictive Modeling, Geospatial Data Analysis, Generative Models, Physics-Informed Machine Learning, Artificial Intelligence for Physical Simulations.
Practical programming experience, preferably using machine learning frameworks such as Tensorflow or PyTorch
A proven outstanding research and innovation track record.
Preferred Technical and Professional Expertise
Experience in roles in academic or industrial research institutions.
Demonstrated ability to create / drive both long running projects and quick prototypes ?
e.g., research demos, open-source projects.
Experience with developing technologies for a cloud-based environment.