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The Institute of Data Science at Maastricht University, the Netherlands, is looking for a post-doctoral researcher to work on projects in computational social sciences. Specific problems include evaluation of intervention techniques in simulated online social environments, identification of online influence campaigns, and reassessing the conflict between data privacy and accountability on social platforms. Of particular interest are topics that acknowledge cross-platform and multi-platform processes and the interplay between offline events and online interactions.
The position responsibilities will include:
1. Conducting data-driven research in computational social sciences.
2. (Co-)authoring scientific, peer-reviewed papers for top conferences and journals.
3. Being involved in proposal writing.
4. Contributing to department teaching activities.
1. Ph.D. degree in computer science or a closely related field.
2. Strong computational and data science skills evidenced by peer-reviewed publications.
3. Experience working with huge datasets. Familiarity with social network analysis is a plus.
4. Ability to program in Python.
5. Excellent ability to write, present and communicate in English.
Fixed-term contract: 2 years.
**** CONDITIONS OF EMPLOYMENT
The full-time position is offered for a period of 2 years subject to annual review. Renewal beyond the initial 2-year appointment is possible subject to the existence of funding and satisfactory performance.
The salary will be set on a scale of 11 (between € 3.821 and € 5.230 gross per month) depending on education and relevant work experience. On top of this, there is an 8% holiday and an 8.3% year-end lowance. The terms of employment at Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. Non-Dutch applicants could be eligible for a favorable tax treatment (30% rule).
The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website www.maastrichtuniversity.nl > About UM > Working at UM
The intended starting date of this position is as soon as possible.
Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. Maastricht University has around 22,000 students and circa 5,000 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. The University hosts 6 faculties: Faculty of Health, Medicine and Life Sciences, Faculty of Law, School of Business and Economics, Faculty of Science and Engineering, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience.
The Institute of Data Science (IDS) at Maastricht University is a research center embedded in the Faculty of Science and Engineering led by distinguished professor Michel Dumontier. IDS is an interfaculty institute consisting of a core team of data science experts that cooperate closely with researchers across disciplines such as medicine, life sciences, social sciences and humanities, business and economics, knowledge engineering, and smart services. The mission of the Institute of Data Science is to foster an interfaculty environment for collaborative innovation in the development and application of data science technologies.
The Faculty of Science and Engineering (FSE). Maastricht University heavily invests in the growth of its STEM research and education. The Faculty of Science and Engineering – which houses the Department of Data Science and Knowledge Engineering - is one of the focal points of these developments. Within the Faculty of Science and Engineering, over 260 researchers and more than 2,700 students work on themes such as fundamental physics, circularity and sustainability, data science, and artificial intelligence.
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