State of the art Machine Learning and Computer Vision approaches are a necessity in automated drone and helicopter utility inspection. We are looking for researchers who are willing to apply the scientific method to the development of industry leading next-generation RGB-camera, HyperSpectral and LIDAR data processing systems. We expect a hands-on approach to bringing systems from bleeding-edge research to operational prototypes and into client-facing production.

We offer a unique opportunity to work in a challenging and exciting field, alongside a team of experts in the field. You will be provided with a chance to apply the latest and greatest algorithms alongside your ideas and further improvements in an environment where your opinions are really taken to heart. The work you will embark on here, will not only develop the future of remote sensing, but also the future of utility drone automation.

A prospective applicant should have:

• A Masters or Ph.D. in Computer Science, Physics, Engineering, Mathematics, or related field.
• Experience in the following fields: Computer Vision, Deep Learning and other Machine Learning methods, Object Detection, Few-Shot learning approaches, automated vegetative analysis and multi-spectral data analysis.
• Strong experience in coding with Python and related frameworks: NumPy, SciPy, SciKit-Learn, Pandas, Jupyter, PyTorch (or similar machine learning frameworks: TensorFlow, Keras, etc.)
• Experience in working as part of an agile software development team with a focus on continuous delivery. Here ability to transfer experimental models into working solutions, and integrate them with existing systems is a must.
• Good communication and writing skills with a strong ability to translate leading edge research ideas into client facing propositions. We expect excellent English language skills, a working knowledge of Finnish is also a nice bonus

Bonus skills:

• Experience in working with large scalable systems in the cloud (AWS S3, Kubernetes, Docker, AWS SageMaker, AWS EC2)
• Strong statistical data analysis and information visualization skills (matplotlib, Bokeh, Seaborn, Dash, etc.)
• Experience in working with Geo-Spatial and LiDAR data (GeoJSON, GeoPandas, Shapely, GDAL, PDAL, Fiona, laspy)
• Experience in writing beautiful, straightforward, and easily maintainable code as part of a collaborative team (Git, RESTful APIs, etc.) 
• Track record of publications at relevant conferences is a bonus (NeurIPS, CVPR, ICCV, ICRA, etc.)