Topic of the project The successful candidate will work in the field of neuro evolution and autonomous learning. This paradigm expects machines to explore and observe the environment, make predictions and ultimately learn much more like their human counterparts. Genetic algorithms are used to make systems able to autonomously learn. This work involves questions about forming memory and representations, using representations to inform decision making, theory of mind, artificial consciousness, and allows for comparisons to other machine learning methods like deep or reinforcement learning
To be admitted to doctoral studies in Microdata Analysis, the applicant must meet both the general and specific entry requirements and have the capacity required to benefit from doctoral studies in this field
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Teaching Positions: Application Information Vacant Positions Vacant Positions Vacant Position Share × Share this page PhD position in Microdata Analysis, specialising in Artificial Intelligence Social Link E-mail Own message (optional) We also send information about the page in the message. Send PhD position in Microdata Analysis, specialising in Artificial Intelligence Share this page Page Content Ref HDa 2.3.1-2020/368 Are you interested in contributing to future research about neuro evolution and autonomous learning? We now offer a fully funded PhD position in Microdata Analysis. Subject and research areaMicrodata Analysis is a multidisciplinary field involving collection, modeling, compilation, and interpretation of large data sets, together with underlying algorithms, methods, and techniques, as well as its application to decision making. Microdata Analysis at Dalarna University is predominately applied to health, environment, energy, transport, infrastructure and industry. The PhD programme gives broad general knowledge and attractive specialist competence in Business intelligence and Business analytics, opening opportunities for both an academic career and work in e.g. research institutes, management or consulting. The programme is suited for applicants with a degree at the second-cycle level in disciplines such as computer science, informatics, engineering, statistics, economics, or geography. Topic of the projectThe successful candidate will work in the field of neuro evolution and autonomous learning. This paradigm expects machines to explore and observe the environment, make predictions and ultimately learn much more like their human counterparts. Genetic algorithms are used to make systems able to autonomously learn. This work involves questions about forming memory and representations, using representations to inform decision making, theory of mind, artificial consciousness, and allows for comparisons to other machine learning methods like deep or reinforcement learning. As a PhD student you will primarily focus on your studies and research. 20% of your time may also be spent on departmental duties, often teaching, at the Faculty of Data and Information Sciences. Qualifications To be admitted to doctoral studies in Microdata Analysis, the applicant must meet both the general and specific entry requirements and have the capacity required to benefit from doctoral studies in this field. General Entry Requirements The General Entry Requirements for admission to doctoral studies are as follows: 1. A degree at master level, 2. Completion of 240 university credits of which 60 are at advanced level, or 3. Equivalent skills acquired through other means in either Sweden or another country. Specific Entry Requirements Specific Entry Requirements require that the applicant has successfully completed at least five courses in the following subjects: Database Systems - 7.5 credits Data Analysis and Statistics - 7.5 credits Artificial Intelligence - 7.5 credits Programming - 7.5 credits Mathematics - 7.5 credits Economics - 7.5 credits Optimization Techniques or Probability Theory - 7.5 credits Decision Theory - 7.5 credits SelectionSelection from among applicants who meet the entry requirements shall be made based on the criteria in the general study plan. Candidates with background from biology, evolution, cognitive science, or computer science are welcome. Working knowledge of C++ and Python are required. Knowledge in computer modelling and math present an advantage. In order to succeed as a PhD student, you need to be able to collaborate well with others, which includes both sharing your knowledge and to be open to guidance and tutoring by others. You also need to be a motivated self-starter who is able to take initiative and work independently towards a long-term goal. English language skills, both written and oral is a must. The assessment of candidates is also based on previous study results and independent work at master’s level. Employment The PhD position is a full-time employment (fixed term) in accordance with the Higher Education Ordinance (chapter 5). Salary stipulated by local collective agreement. Dalarna University is situated in two cities. The successful candidate with be primarily placed in Borlänge. This studentship is available for European and non-European citizens. How to apply Your application should contain: Cover letter and CV Copies of diploma supplement and grades Previous independent writing such as thesis Research statement (1-2 pages where you are expected to reflect on the research topic and your knowledge and interest in the area) Two academic references If you have any technical issues or questions regarding submission of your application, please contact email@example.com Please submit your application on no later than 2020-06-15. In case of disagreement between the English and the Swedish version of this announcement, the Swedish version takes precedence. If you want to learn more about Dalarna University as an employer, visit https://www.du.se/en/about-du/career-opportunities/why-work-here/ We respectfully decline all offers from advertising companies and recruitment firms. By working at Dalarna University, you can help create opportunities so that everyone can attain a higher education. Regionally and globally, we create open pathways to knowledge for a good society. We work to ensure our programmes and courses remain of relevance and of high quality, while our research is conducted in close collaboration with external partners. We have 800 staff members and 15 000 students, as well as a great many collaborative partners. Do you want to effect change in the world with us? Contact persons Prof. Yves Rybarczyk Study director of the PhD programme in Microdata Analysis +46 (0)23-77 83 99 firstname.lastname@example.org Märet Brunnstedt Doctoral Studies Coordinator email@example.com Patrick Kenger Akademichef firstname.lastname@example.org Apply Dalarna University saves some data as cookies to enhance and personalize your visit to our website. Learn more about cookies.
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