Full Professor In Applied Statistics

Do you have a compelling and refreshing vision on statistical science - are you eager to move beyond traditional boundaries and conventional views, and lead the way in exploring emerging scientific challenges? We are looking for a full professor in Applied Statistics with a broad disciplinary expertise, strong mathematical background, and natural drive for pursuing applications.

The scientific direction of this full professor role is to develop statistical theory and data-analytic methods for the analysis of complex, large, and/or high-dimensional data sets. The focus of the research is to provide a more systemic view or a full breadth of all interrelationships of the collected data simultaneously, instead of determining inference or information on one specific feature of the data.

Specific topics of interest that would be related to these research goals include Bayesian analysis, causal inference, data harmonization, distributed analysis, network analysis, predictive analytics, spatial statistics, statistical learning, and survival analysis. Data collection techniques and design of complex studies, e.g., experimental design, nonprobability-based sampling, and surveys, are of interest as well.

Strong disciplinary expertise, a broad vision on applied and fundamental research in statistics (rooted in deep knowledge of the classical statistical methods and underpinnings, but also encompassing modern data-analytic techniques), and a keen eye towards applications are imperatives to achieve the above ambitions.

It is further crucial to proactively connect with scientists in other disciplines who use and analyze data and to forge strong links with data-intensive sectors in industry and society, for example in the area of high-tech systems, health, smart mobility, consultancy services, and governmental agencies.

Key responsibilities of the position are:

• Develop internationally leading research in the research area described above and actively publish in international high-impact journals.
• Initiate, acquire and coordinate (multidisciplinary) research projects through external funding.
• Strengthen connections and collaborations with other researchers and research programs within the Mathematics & Computer Science (M&CS) department, TU/e, The Netherlands, and abroad.
• Actively develop a network with external partners which support the research and innovation in applied statistics both financially and content wise.
• Actively contribute to the workshop program of EURANDOM.
• Develop, teach, and coordinate courses for the BSc, MSc, and PhD education programs of the M&CS department as well as for the service education, and be responsible for renewing these courses.
• Supervise BSc, MSc, and PhD students in mathematics and data science.
• Perform managerial and/or administrative tasks for the Stochastics, Probability and Operations Research (SPOR) cluster, the Mathematics domain, and the M&CS department.
• Provide leadership to the professionals of the Teaching and Research Institute for Data Science Analytics (TRI-DSA), activities and directions where appropriate.

SPOR cluster

The Department of Mathematics and Computer Science (M&CS) is organized in three different domains: Mathematics, Computer Science, and Data Science. Each domain consists of several clusters. The Mathematics domain has three clusters: Center for Analysis, Scientific Computing and Applications (CASA), Discrete Mathematics (DM), and Statistics, Probability and Operations Research (SPOR).

The SPOR cluster currently consists of four full professors, three associate professors, 14 assistant professors, six teachers, two part-time professors, and around 45 PhD students and post-docs. SPOR focuses on four themes, namely statistics, probability, stochastic operations research, and combinatorial optimization. These themes are basic mathematical disciplines which form the foundations of many of the developments in modern fields such as machine learning, complex dynamic systems, data-driven decision support and optimization, and resilient network design.

At a high level, researchers in SPOR explore the underlying mathematical structure and dynamics of large-scale complex systems, and develop effective methods to analyze and optimize them. These systems are invariably inspired by real-world applications. Thus, SPOR has a double perspective: the research is aimed at advancing theoretical and methodological foundations, while at the same time SPOR maintains strong connections with society, industry and other scientific domains. See https://spor.win.tue.nl for further details.

SPOR widely contributes to the education programs of M&CS in mathematics, computer science, and data science. SPOR also provides extensive service education to other departments at TU/e, and strongly contributes to MasterMath, a joint educational program in which all Dutch universities participate.

Teaching and Research Institute for Data Science Analytics

The Teaching and Research Institute for Data Science Analytics (TRI-DSA) is closely connected to the SPOR cluster, and focuses on innovation, impact, and valorization of statistical and data-analytic methods. The statisticians of TRI-DSA work with external customers on solutions for statistical data science challenges (e.g., performing data analyses, developing software, innovating methods) and provide professional education on statistical and data-analytic methods. TRI-DSA offers a unique platform to pursue collaboration in statistical data science with professionals in the health domain (e.g., industry, hospitals, registries). The full professor is expected to provide leadership to the statisticians of TRI-DSA by taking ownership of these opportunities, developing new initiatives, and contributing to long-term strategic goals on innovation and impact. See https://tri-dsa.win.tue.nl for further details.

Requirements:

• Enthusiastic and inspiring researcher and educator, with a PhD in the area of Statistics, or a comparable domain.
• Sustained track record of high-quality academic research and international recognition and visibility, as evidenced by invited lectures at major conferences and renowned institutes.
• A strong mathematical background, deep understanding and appreciation for foundational research, and ability to capitalize on research connections and strengthen them to their full potential.
• Significant track record in initiating research projects and project acquisition.
• Strong interest in pursuing multi-disciplinary collaborations and applications.
• Didactic qualifications and ability to teach, demonstrated by ample experience and successful educational track record. Informed vision on teaching and learning in the area of Statistics and Data Science.
• Strong cooperation skills, collegial style, professional attitude, and ability to work in diverse teams.
• Effective communication and leadership skills aimed at enabling people to develop and creating synergy, including coaching and mentoring of students and staff, leading a project, managing a group or chairing a committee.
• Excellent (written and verbal) proficiency in English. 

Salary Benefits:

A highly rewarding job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Salary in accordance with the Collective Labour Agreement for Dutch Universities.
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• A dedicated mentoring program to help you get to know the university and the Dutch (research) environment.
• High-quality training programs for academic leadership and teaching.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and partner career support.

38 hours per week

De Rondom 70