PhD Candidate in Machine Learning for Dynamical Systems
2 weeks ago
School of Electrical Engineering and Computer Science at KTH Project Third-cycle subject : Electrical Engineering
The project is in collaboration with a Swedish company for state-of-the-art statistical signal processing and machine learning based design and analysis of dynamical process and time-series. We will strive to develop data-driven state estimation and tracking methods beyond Kalman and Particle Filters. We will also develop classification and clustering of complex dynamical processes. The associated machine learning methods preferably will be unsupervised and semi-supervised. Supervision: Assoc. Prof. Saikat Chatterjee, co-supervisor Prof. Magnus Jansson What we offer- The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from all over the world .
- A workplace with many employee benefits and monthly salary according to KTH’s Doctoral student salary agreement.
- A postgraduate education at an institution that is active and supportive in matters pertaining to working conditions, gender equality and diversity as well as study environment.
- Help to relocate and be settled in Sweden and at KTH .
- passed a second cycle degree (for example a master’s degree), or
- completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
- acquired, in some other way within or outside the country, substantially equivalent knowledge
- independently pursue his or her work
- collaborate with others,
- have a professional approach and
- analyse and work with complex issues.
- CV including your relevant professional experience and knowledge.
- Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above) . Translations into English or Swedish if the original document is not issued in one of these languages. Copies of originals must be certified .
- Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.
sach @kth.se
In your application, please refer to myScience.org and reference JobID 2883813 .
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