Internship – Data scientist
Alteia provides tremendous career opportunities to professionals willing to work hard on meaningful challenges alongside a talented team.
By joining Alteia, you’ll participate in the transformation of key industry sectors that are increasingly relying on imagery and artificial intelligence to drive their businesses. You’ll have a unique chance to shape and implement your ideas as part of a leading, fast-growing, cutting-edge company! In addition, you will be surrounded by professionals who have an exceptional background and amazing stories.
We encourage out-of-the-box ideas and incentivize our teams to develop their creativity. As a result, Alteia can give you a unique opportunity to gain valuable and challenging experience in a fast-growing business with passionate, easy-going, enthusiastic people.
It is in technical excellence and perpetual innovation that we recognize ourselves.
The Alteia Platform is the cloud-based solution that enables enterprises to rapidly and flexibly access and prepare gigabytes of visual data (images, point clouds, videos, etc.) with prebuilt annotation/labeling tools. It allows our customers to build and manage A.I models without writing code using an intuitive user interface. Then deploy applications within weeks with customizable validation processes and continuous improvement workflows. From there, they can drive company-wide results by seamlessly publishing predictive insights to enterprise systems or custom business applications.
Within our Toulouse offices, you will join a team of data scientists specializing in deep learning, image processing, and geomatics, in charge of R&D on data analysis tools deployed on the delair.ai platform. The team’s expertise is in analyzing data from various sources: images of drones, LIDAR point clouds, CAD models, etc.
Three themes are considered according to your profile:
1. Deep learning applied to 3D data.
Your main task will be to design algorithms for the semantic segmentation of point clouds. Point clouds from LIDAR sensors and/or photogrammetric processing generally have large sizes and require robust and efficient algorithms to be analyzed.
First, you will learn about a semantic segmentation model developed internally to familiarize yourself with the problem. Secondly, you will have to implement and compare different neural network architectures adapted to this type of data: deep nets, 3D CNN, point-net, CNN graph, etc.
2. Deep learning applied to semantic image segmentation.
Your main task will be to design algorithms for semantic segmentation on orthorectified images from a drone survey of industrial infrastructure (agriculture/mining and quarry).
First, you will learn about a semantic segmentation model developed internally to familiarize yourself with the problem. Then, as a second step, you will have to implement and test different neural network architectures that use semi-supervised or weakly supervised approaches.
3. Deep learning applied to object detection on images.
Your main task will be to design algorithms for semantic segmentation on images from a drone survey of industrial infrastructure (power lines).
First, you will learn about object detection models developed in-house to familiarize yourself with the problem. Secondly, you will have to implement and test different neural network architectures that aim to improve performance through a so-called multi-view approach that effectively uses other points of view on the same object.
You are: Committed. Rigorous. Autonomous. Persistent for the purpose of succeeding.
Qualifications and skills:
- Student in the last year of a Bac + 5 type Master 2 or Engineering School specializing in image processing or data science.
- Machine Learning / Deep learning concepts.
- Experience with a machine learning library (PyTorch, Tensorflow, sklear).
Languages: English: fluent. French: Fluent. Excellent verbal and written communication in both.
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