At KSAT we are operating a massive global ground network of antennas supporting satellites and rockets in space. We're also providing advanced monitoring services based on expert analysis of satellite data, providing detailed information about events like oil spills, illegal fisheries, illegal logging in rainforests, landslides and ice conditions to customers around the world.
Huge growth in international satellite market
As more and more satellites are being launched, many in large constellations, the traffic on our network is dramatically increasing. This creates a need for a higher degree of automation of both operations and monitoring, as well as modern interfaces (both M2M and web-based) that meet our customers' needs. In addition, to be able to handle the amounts of data available in the near future, we want to extend our Machine Learning platform to a wider variety of satellite data, especially optical data.
6 summer weeks with possibility of part-time jobs
We primarily want to put together smaller teams (2-3 people) to solve one or more of the tasks. Which part of the summer you work and how long is flexible and agreed with the individual, but we consider 6 weeks as a minimum to be able to achieve concrete results. It may also be possible to continue after the summer in the form of a part-time job if both parties see it as appropriate. If you are still reading and you want to know more, follow these links to our summer intern announcements where you also can find out how to apply.
In general, the jobs will consist in the design, implementation, verification and documentation of tasks that include functionality for obtaining measurements from existing equipment (XML over TCP sockets) and storage for time series database, functionality for generating new information through measurement analysis, as well as database with associated API and clients for manipulation and visualization.
We are looking for students who have programming experience (Python, Java or Perl), through study, hobby or previous jobs. Experience with JetBrains tools and / or databases is an advantage.
Read more here: https://www.finn.no/job/fulltime/ad.html?finnkode=170151612
You will work together in a team where everyone works specifically on ship detection / classification, and the solutions you create is intended to be part of our services in the future. KSAT's dataset is unique, but not specifically adapted to deep learning, and we do not have a training dataset suitable for this task. A large part of the task is therefore to automate and quality-assure training data, and practical data management / pre-processing.
We are looking for students with experience in ML/Deep learning, that has two years or less left of their master's degree. Relevant courses at UiT is FYS-2021, FYS-3012 and FYS-3033. Other relevant expertise such as image processing, Earth Observation, information technology, etc., is an advantage.
Read more here: https://www.finn.no/job/fulltime/ad.html?finnkode=171675257