Are you interested in studying networks and using methodology at the cross-section of business analytics, econometrics and computer science? The Business Analytics section at the University of Amsterdam Business School invites applications for a PhD position in Network Statistics and Machine Learning. We are looking for candidates with the ambition to work and succeed at the highest international academic level.

The main topic of research is network analysis and modelling using statistical and machine learning tools. Network data are ubiquitous in finance, social media, the economy, and business. Social networks play an increasingly important role in society. For example, the Reddit community WallStreetBets hyped the stock of GameStop (GME), causing a short squeeze and extremely volatile stock prices in early 2021. Similarly, statements made on social networks such as Twitter have been shown to impact public and voter opinions. Exemplifying how social networks directly affect the economy, this project focusses on studying network data with a specific interest in modelling and understanding how networks change over time. Change detection in an online fashion is a challenging task in networks of large size, a common property of social networks.

In this research, the candidate will first investigate and develop interpretable network analysis approaches using statistical models and test them on real-life data. Then geometric deep learning approaches for the tasks like node classification, link prediction and graph classification will be developed with change detection ability. In the final phase of the project, the candidate should bring together two families of methods and design an optimized algorithm that is both interpretable and yields a high performance in network change detection.

The PhD student will work in close collaboration with the supervisory team and other faculty on the tasks.

The supervisory team will consist of dr. Inez Zwetsloot (ABS), dr. Simon Trimborn (ASE) and dr. Stevan Rudinac (ABS).

What are you going to do?

• Develop novel interpretable statistical models for network analysis;
• develop novel deep-learning approaches for node classification, link prediction, and community detection in network data;
• create open data and software tools for the envisioned network analysis tasks;
• present research findings at international conferences;
• write up findings for publication in international journals;
• pursue and complete a PhD thesis within the appointed duration of four years;
• attend classes and seminars (including those offered at other universities) to develop thinking and research skills further;
• participate in and contribute to departmental research functions (PhD Day, research seminars, and research meetings);
• assist in knowledge dissemination activities;
• participate in teaching-related activities (to a limited degree), including undergraduate tutorials and the supervision of MSc and/or BSc thesis projects.

Formal requirements:

• Masters' degree in Statistics, Econometrics, Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field (expected to finish by September 2023)

Task-related requirements:

• Excellent communication skills in English, both oral and written, ideally with experience writing for a scientific audience;
• willingness and motivation to independently formulate research projects and carry them through to completion;
• mathematical skills, data analytics skills, and a strong willingness to develop these skills further;
• excellent programming skills in one or more of the following languages: Python, R, C, C++;
• preferably experience with at least one of the following: network data analysis, deep learning libraries such as PyTorch or TensorFlow, timeseries modeling and prediction, high-performance computing.3

Additional requirements:

• Preference is given to candidates with some research experience (e.g., Master thesis and/or research assistant experience);
• strong commitment to methodological rigor and scientific integrity;
• energy and passion for statistics and machine learning;
• intellectual curiosity, eagerness to learn, and openness to criticism;
• willingness to participate in disseminating research results and valorization.

The employment contract will be for four years with an initial period of 18 months, with an intermediate evaluation after 18 months and a possibility to extend it for 30 months (in total, four years). End-result should be a PhD thesis. An educational plan will be drafted that includes attendance of courses and (international) conferences. Preferred starting date is 1 September 2023.

The gross monthly salary will range from €2,541 in the first year to €3,247 in the last year. The Collective Labor Agreement for Dutch Universities is applicable.

Additionally, the University of Amsterdam offers excellent benefits and various schemes and regulations to promote a good work/life balance, such as:

• 232 hours of annual leave based on full-time employment;
• 8% holiday allowance and 8.3% end-of-year bonus;
• Solid pension scheme (ABP);
• Contribution to commuting expenses.

The compensation package is competitive at the European level and includes several secondary benefits. Favorable tax agreements may apply to non-Dutch applicants. To learn more about working at the University of Amsterdam, please check this link and uva.nl/working-at-eb.

What else do we offer?

• A function in which your own initiative and input are strongly valued;
• an enthusiastic and warm team that is open to new colleagues;
• collaboration opportunities in an active and vibrant research environment;
• an inspiring academic and international work environment at the center of Amsterdam;
• opportunities to visit international conferences and research centers;
• opportunity to work from home flexibly.

Faculty of Economics and Business

About UvA
With over 5,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands.

About UvA Economics and Business
Education and research at UvA Economics and Business (EB) cover a wide range of fields, including economics, data science, business administration, business analytics, accountancy, control, econometrics, finance, and entrepreneurship. This is organized in 2 Schools: the Amsterdam Business School (ABS) and the Amsterdam School of Economics (ASE). Over 7,000 students are enrolled in our UvA Economics and Business programs, and around 500 employees provide education and support. You will primarily work in the Amsterdam Business School that acquired the triple-crown accreditation (AACSB, AMBA, EQUIS), awarded to only 1% of business schools worldwide.

• Find more information about Economics and Business on uva.nl/eb.
• Find more information about the Amsterdam Business School on abs.uva.nl.
• Find more information about the Amsterdam School of Economics on ase.uva.nl.

About the department

The department of Business Analytics of the Amsterdam Business School focuses on research in a wide range of areas of business analytics, including artificial intelligence, digital business, statistics and operations research.

The members of the department have published their research in the top-tier academic journals, such as Operations Research, Management Science, Mathematical Programming, Journal of Machine Learning Research.

The members of the section are also involved in teaching in undergraduate, master, and research master level programs, as well as in executive education, and uphold strong relationships with industry, business, and public sectors.

Our staff is associated with various research initiatives and platforms, e.g. the Analytics Academy, the brand new Analytics for a Better World initiative, the Institute of Business and Industrial Statistics (IBIS UvA).