Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Uppsala universitet
- Linköpings universitet
- Umeå University
- Umeå universitet
- Linköping University
- Lulea University of Technology
- Luleå University of Technology
- Chalmers University of Technology
- Chalmers tekniska högskola
- Linkopings universitet
- Luleå tekniska universitet
- Lunds universitet
- Nature Careers
- SciLifeLab
- Stockholm University
- Stockholms universitet
- Sveriges lantbruksuniversitet
- 7 more »
- « less
-
Field
-
of excellent research a prominent place in Scandinavian mathematics. The department consists of three divisions: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division
-
qualifications You have graduated at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced
-
be in advanced courses in computer science, mathematics, AI, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected
-
automata, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
-
- 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
-
build the sustainable companies and societies of the future. The department of Computer Science, Electrical and Space Engineering at Luleå University of Technology (LTU) is offering two PhD student
-
, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
-
Computer Science Electrical and Computer Engineering Mechanical Engineering Applied Mathematics Applied Physics Statistics and Optimization A strong background in robotics, machine learning, and control is essential
-
qualifications You have graduated at Master’s level in computer science or completed courses with a minimum of 240 credits, at least 60 of which must be advanced courses in computer science, mathematics, AI
-
, computer science, electrical engineering, applied mathematics, machine learning, or in a similar field, or have completed at least 240 credits in higher education, with at least 60 credits at Master’s level