Application Deadline: July 15, 2020
Program unggulan : Program English Speaking and Conversation
Brief Description
- University or Organization: TU Wien
- Department: NA
- Course Level: PhD
- Award: 30.754 EUR per year
- Access Mode: Online
- Number of Awards: Not Known
- The award can be taken in Austria
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Eligibility
- Eligible Countries: If you want to know about nationality, please directly contact the employer.
- Acceptable Course or Subjects: PhD program in Artificial Intelligence (Description Logics, Answer Set Programming, Knowledge Representation, and Reasoning, Reasoning about Actions and Change, Database Theory).
- Admissible Criteria: To be eligible, applicants must meet the following criteria:
- Must have a degree in Computer Science, Mathematics, or other closely related fields.
- Must have a very strong study record, especially in foundational topics (like discrete mathematics, logic, logic programming, algebra, a theory of computation, computational complexity, combinatorics, graph theory, automata theory, data structures, and algorithms).
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How to Apply
- How to Apply: In order to apply for the opportunity, all eligible applicants must send their application to Dr Mantas Šimkus (simkus-at-dbai.tuwien.ac.at).
- Supporting Documents: Must provide a motivation letter, curriculum vitae, transcripts (academic record) showing high performance in prior studies, abstract of the Master thesis
- and 2 letters of recommendation.
- Admission Requirements: To become a part of this position, applicants must have a previous year degree.
- Language Requirement: Candidates should have excellent English writing skills.
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Benefits
The Vienna University of Technology will offer the following benefits:
- Provide employment for up to 3.5 years, with Dr Mantas Šimkus as a PhD advisor.
- Gross salary of approx. 30.754 EUR per year (approx. 22.506 EUR per year after taxes in basic circumstances)
- Candidates would join the LogiCS doctoral program, which offers top research expertise, and a stimulating and supportive environment.
- A research and study environment that is friendly and gender-balanced.
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