Department of Mathematics, Aarhus University

2156 13119Position ID: MATHAU-ASSOCPROF [#13119, 1012813]
Position Title: Associate professorship(s) in data science and statistics
Position Type: Tenured/Tenure-track faculty
Position Location: Aarhus, N/A 8000, Denmark [map]
Subject Area: Data Science and statistics
Application Deadline: 2019/02/01 (posted 2018/11/08, listed until 2019/05/08)
Position Description:    

The Department of Mathematics, Faculty of Science and Technology, Aarhus University, invites applications for 1-2 associate professorships in data science and statistics (Call no. 1012813). The successful candidate will be part of the Stochastics Group at the Department.

The position is available from 1 August 2019.

The Stochastics Group has a strong theoretical profile in probability theory and mathematical statistics. Over recent decades, the group has hosted two centres of excellence, involving applications in turbulence, finance, bioinformatics and bioimaging. The Stochastics Group also has close ties to CREATES: Center for Research in Econometric Analysis of Time Series at the Economic Department. The Department of Mathematics wants to continue and expand the interdisciplinary research in close interplay with the surrounding community.

The Stochastic Group has 10 faculty members divided into probability and statistics, and besides this there is a small group offering statistic consultancy to the biosciences.

For the open position, we search for a person with a broad knowledge of mathematical statistics, in particular, we invite applications from persons with a research interest in modern statistical theory of big data and high dimensional problems.

The University is undertaking a major initiative to increase the number of graduates with experience in Digitalisation. The Department of Mathematics is an important part of this initiative and will over the next few years see a significant increase in the number of researchers within the area of analytic data science. The Department is planning a major educational effort in data science, including a new interdisciplinary programme, both at bachelor and master level. The planned Data Science programme focuses on mathematical and statistical competences and involves also a broad range of topics from applications. The successful candidate will take active part in the planned Data Science programme. Furthermore, the Faculty of Science and Technology inaugurated last autumn the new DIGIT initiative, an interdisciplinary centre for research in digitalisation, big data and data analytics, where the Department of Mathematics also plays an important role.

The successful applicant is supposed to take part in all aspects of a university position, including research, fundraising and administration. The applicant is expected to participate actively in the teaching at all levels and to supervise students at the master's and PhD level.

Applicants should have a strong record of original scientific research at a high international level. Applicants are also expected to document their experience with all facets of university teaching and supervision.

For further information, please contact head of department Jacob Schach Møller, email jacob@math.au.dk; phone +45 87155721.

Referees can send the letters directly to the Science and Technology Human Resource Department at emply.st.hr@au.dk. Referees are asked to state the name of the applicant in the subject field of the email.

Aarhus University offers Relocation service to International researchers.

Application procedure Shortlisting is used. This means that after the deadline for applications and with the assistance from the assessment committee chairman, and the assessment committee if necessary, the head of department selects the candidates to be evaluated. The selection is made on the basis of an assessment of who of the candidates are most relevant considering the requirements of the advertisement. All applicants will be notified within 6 weeks whether or not their applications have been sent to an expert assessment committee for evaluation. The selected applicants will be informed about the composition of the committee and will receive his/her assessment. Once the recruitment process is completed a final letter of rejection is sent to the deselected applicants, including the main considerations emphasized during the selection process.

Formalities and salary range: Science and Technology refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found on the website.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Finance and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities. (in Danish).

Salary depends on seniority as agreed between the Danish Ministry of Finance and the Confederation of Professional Associations.

All interested candidates are encouraged to apply, regardless of their personal background. Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.


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Contact: Jacob Schach Møller, +45 87155721
Email:
Postal Mail:
Ny Munkegade 118, Building 1530
DK-8000 Aarhus C
Denmark
Web Page: http://math.au.dk/en/about/vacancies/?tx_peoplexs_pi1%5Bid%5D=1012813&tx_peoplexs_pi1%5BportalId%5D=5283&tx_peoplexs_pi1%5Baction%5D=show&tx_peoplexs_pi1%5Bcontroller%5D=Vacancy&cHash=e7fced8783c3e969

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