1-2 PhD positions are available at the Department of Computer Science, University of Copenhagen (DIKU). The PhD student(s) should start between August 1st 2016 and January 1st, 2017.
The PhD students will be part of strong team in algorithms and machine learning at DIKU, working on theoretical computer science published in e.g. STOC, FOCS, SODA, NIPS, ICML, AISTATS and COLT, but also conducting experimental work in cooperation with industry partners. We have access to huge data and the experimental work is expected to have impact on at least millions of people. The PhD student(s) and the team are part of the DAnish Center for Big Data Analytics and Innovation (DABAI). DABAI involves researchers from University of Copenhagen, Technical University of Denmark and Aarhus University. The PhD student(s) will work with colleagues from all the involved universities but will be anchored at the Algorithm research group at University of Copenhagen. The team at DIKU - involved in DABAI - is involved in other strong Big Data initiatives. More information about these initiatives and the team can be found at https://sites.google.com/site/dabaidiku/ <https://sites.google.com/site/dabaidiku/> *Expectations* The PhD student(s) should - during the project - produce strong theory papers, experimental papers, some implementation, and cooperate with other researchers from different departments and universities, in addition to cooperation with industry partners. That includes working on theory and implementation of algorithms for the domains in focus in the project. The primary industry partner/focus for the team at DIKU will be companies making software for education. Therefore, the cooperation with companies will e.g. focus on optimizing personalized learning and recommender systems for efficient decision support in educational learning. *Qualifications* Applicants should hold an MSc degree - from an internationally recognized University. The MSc thesis should be in an area relevant for the project, e.g., algorithms, machine learning, mathematics, or information retrieval. Candidates who do not yet have their MSc degree, but who are expecting to be able to enroll August 1st, 2016 or latest January 1st, 2017 should specify the expected date of graduation, confirmed by their main MSc supervisor. Among the qualified candidates, criteria to be considered include, among others: - Published research papers at highly recognized venues - High grades in algorithms, mathematics, machine learning, and other relevant courses - Recommendations from highly recognized researchers in algorithms and machine learning - Previous experience in Big Data Analytics implementation, - Excellent English skills, written and oral (if coming from non-English speaking countries, proof of passing English language tests and/or graduate education in English) - Good communication and interpersonal skills Applicants must document their successful MSc studies by a high-grade average. If the applicant’s MSc work has resulted in a publication (accepted or in draft) this is considered a strong advantage. The applicants should submit as part of the application a recommendation letter from one of the researchers at https://sites.google.com/site/dabaidiku/. To get such a recommendation, email Henrik Hochreuter: [email protected] and specify which researcher you wish to get in contact with, and also attach the necessary information needed to make a recommendation (e.g. cv, grades transcript). *Application * Applicants are requested to submit their application below including: - A cover letter (max. 1 page) including two lines of motivation, stating when the applicant can start, and any information needed to read and understand the remaining appendix. - Recommendation from one of the researchers at DABAI as stated above. - Curriculum vitae (max. 2 pages) - List of publications (if relevant) incl. papers accepted or submitted for publication and title of thesis. - Title and abstract of MSc thesis - Transcript of university examinations (in English) - Contact details of 1-2 persons for references - Letters of recommendation from researchers not associated DABAI at DIKU. *Procedures and shortlisting * After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. An expert assessment committee decides if the applicant is qualified or not. Selected applicants are notified of the composition of the committee and each applicant has the opportunity to comment on the part of the assessment that relates to the applicant himself/herself. The Head of Department, based on the recommendations of the assessment committee, will make the final selection of successful candidates. *Terms of salary and employment* Terms of appointment and payment are in accordance with the agreement between the Danish Ministry of Finance and the Danish Federation of Professional Associations (AC). The appointment is for a period of 3 years and must lead to a dissertation. The University of Copenhagen wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of personal background. *The deadline for applications is June 15, 2016.* Applications received after the deadline, or with insufficient documentation or otherwise not complying with the above requirements, June not be considered. It is expected that the successful candidate will be enrolled at the PhD School of the Faculty of Science, August 1, 2016 or latest January 1, 2017. Further information can be obtained via email to: Henrik Hochreuter: [email protected] *APPLY NOW* <https://ssl1.peoplexs.com/Peoplexs22/CandidatesPortalNoLogin/ApplicationForm.cfm?PortalID=12921&VacatureID=814131> *Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.*
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