Postdocs, ERC Advanced Grant Project FLEX (m/v/x)

Most statistical methods require that all aspects of data collection and inference are determined in advance, independently of the data. These include when to stop collecting data, what decisions can be made (i.e. accept/reject null hypothesis), and how to measure their quality (e.g. loss function/significance level). This is wildly at odds with the flexibility required in practice! It is a leading cause of the replicability crisis in the applied sciences.

The project aims to develop novel theory and methods of statistics in which all data-collection and decision-aspects may be unknown in advance, possibly imposed post-hoc. Yet the new theory will provide valid small-sample error control and uncertainty quantification. The theory will be based on far-reaching extensions of e-values, e-processes, and the e-posterior, flexible alternatives for p-values and Bayes factors that have been developed over the last five years. Other key topics include anytime-valid confidence sequences, concentration inequalities, martingales and the foundations of statistics (likelihood principle, complete class theorems).

The vacancies are for two three-year postdocs to do research within the FLEX project.

PhD students, ERC Advanced Grant Project FLEX (m/v/x)

Most statistical methods require that all aspects of data collection and inference are determined in advance, independently of the data. These include when to stop collecting data, what decisions can be made (i.e. accept/reject null hypothesis), and how to measure their quality (e.g. loss function/significance level). This is wildly at odds with the flexibility required in practice! It is a leading cause of the replicability crisis in the applied sciences.

The FLEX project aims to develop novel theory and methods of statistics in which all data-collection and decision-aspects may be unknown in advance, possibly imposed post-hoc. Yet this new theory will provide small-sample frequentist error control and uncertainty quantification. The theory will be based on far-reaching extensions of e-values, e-processes, and the e-posterior, flexible alternatives for p-values and Bayes factors that have been developed over the last five years. Other key topics include anytime-valid confidence sequences and the foundations of statistics (likelihood principle, complete class theorems).

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The vacancies are for two four-year PhD students to do research within the FLEX project. The students will join the Machine Learning group at CWI, and receive their PhD degree from Leiden University.

Director Centrum Wiskunde & Informatica (CWI) (m/v/x) 0,8 - 1,0 fte

What will you do?

• As director you are responsible for steering the institute, focusing on the overall strategic goals, leading the development of strategic plans and overseeing their implementation.
• You represent the institute, and maintain relationships with Dutch universities and national, European and international partners in science, industry and society.
• Together with the institute manager, you account for CWI’s results and plans with the board of NWO-I, twice a year.

In more detail:

• You consolidate CWI’s functioning as a national centre, with well-developed collaborative ties to Dutch universities and you contribute to national research agendas and initiatives.
• You advise the board of NWO on CWI’s scientific mission and strategy.
• You effectively promote the interests of CWI and Dutch science in the area of mathematics and computer science.
• You constructively align CWI’s research agenda with its stakeholders, e.g., universities and partners in strategic alliances from public and private organisations.
• You develop policies to establish a diverse and inclusive work environment.
• You ensure a stimulating work environment.
• You are responsible for the institute’s staff and talent policies.

How does CWI’s organizational structure assist you?

• Together with the institute manager (responsible for finance & operations) you are CWI’s directorate. Together with four senior researchers, the directorate forms CWI’s management team, which meets every other week.
• CWI’s institute manager, policy advisor, manager communications, manager HR and several senior scientists with strategic roles report directly to you.
• You regularly meet with CWI’s fifteen research group leaders, with the works council, and with support staff managers. Twice a year you consult with CWI’s advisory bodies, being the national Institute Advisory Council and the international Scientific Advisory Council.

Coördinator QuSoft/Quantum.Amsterdam (m/v/x) 0,8 fte - 1,0 fte

Als Coördinator QuSoft/Q.A ben je de rechterhand van de wetenschappelijk directeur. Dit betekent dat je strategisch meedenkt over de richting van deze organisaties, zowel wat betreft wetenschappelijke ontwikkelingen, als wat betreft de connecties met andere bij quantum-onderzoek betrokken instituten op het Amsterdam Science Park (zoals AMOLF, eScience Center, Nikhef en SURF). Je denkt ook mee over de rol van QuSoft en Q.A in het nationale QDNL-programma, kijkt uit naar financieringsmogelijkheden, zowel nationaal als Europees, en werkt proactief mee aan de totstandkoming van consortia en voorstellen.

De Coördinator stemt regelmatig af met belangrijke personen in de verschillende samenwerkingsverbanden, zoals de Manager Valorisatie bij het CWI en de directeur Marktontwikkeling van de FNWI-faculteit van de UvA, met de directie van het quantum Talent & Learning Center, het Quantum Application Lab (QAL), en het Quantum Software Consortium (QSC), maar bijvoorbeeld ook met de directie van Startup Village en het Amsterdam Science Park. Als Coördinator rapporteer je ook in het Valorisatieoverleg van het CWI.

Een belangrijke rol zal zijn het coördineren van de inbreng en ingroei vanuit QuSoft en het Q.A- ecosysteem bij de invulling en programmering van het nieuwe quantumgebouw, ‘LabQ’, dat naar de huidige verwachting in 2028 opgeleverd zal worden.

Als Coördinator ben je ook verantwoordelijk voor de organisatie van verschillende overleggen (bijv. de DT- en MT-overleggen van QuSoft/Q.A, de 8-wekelijkse “faculty meetings” van QuSoft, het bestuurlijk overleg van QuSoft en overleg met de bij de FNWI betrokken instituuts-directeuren, maar ook voor de team-overleggen binnen Q.A). Daarnaast geef je functioneel leiding aan het supportteam, bestaande uit o.a. een management support officer, een coördinator communicatie & impact voor QuSoft en een coördinator communicatie & community Q.A.

De verantwoordelijkheden op een rij:

•  Lid directieteam QuSoft/Q.A; strategische en organisatorische rechterhand van wetenschappelijk directeur;
•  Mede vormgeven organisatie, o.a. via ontwikkelen van het management team;
•  Samenbrengen partners binnen QuSoft en op Amsterdam Science Park;
•  Sterk consolideren van QuSoft en Amsterdamse Quantum-ecosysteem in het nationale QDNL- programma – aanspreekpunt zijn voor QDNL en ondersteunen van wetenschappers bij rapportages naar QDNL;
•  Meewerken aan grotere Europese consortiavorming en onderzoekfinanciering;
•  Organiseren bestuurlijke overleggen en overleg met wetenschappelijke staf;
•  Verantwoordelijk voor de uitvoerende taken van Q.A en dagelijkse leiding aan het support team

  van QuSoft en Q.A.

PhD on contextualizing generative AI systems in structured data (m/f/x)

Goal of the DataLibra project
Approximately 120 zettabytes of data has been collected worldwide but less than 1% is actually
used. Structured data, e.g. tables, spreadsheets, and relational databases, is prevailing in
organizations and typically informs important decisions in healthcare, governments and finance.
Yet, while AI has demonstrated a high impact on applications on text and images, proportional
progress on structured data is lacking. With the DataLibra project, we aim to close this gap, by
developing AI models and tools for structured data (Table Representation Learning), to help
organizations, of any size, domain, and level of data literacy, get insights from structured data,
efficiently, accurately and securely.

Goal of this PhD project
Following recent developments in AI, large language models (LLMs) have been explored for data
analytics tasks (e.g. text-to-sql), but show limited accuracy in domain-specific contexts with
structured data. In this project, we will investigate and design interactive intelligent systems for
data analytics tasks, while accounting for two key challenges: trustworthiness of the outputs
(factuality), and security constraints of proprietary data contexts as in healthcare, enterprises, and
governments. Potential directions to explore are agentic systems, retrieval augmented generation,
(instruction) fine-tuning, and others.

What you will be doing
 Inform a research agenda on the PhD topic for a timespan of four years.
 Develop methods and systems for contextualizing generative AI for analytics over
structured data.
 Actively collaborate with other researchers in the DataLibra project (students, 4-5 PhDs,
postdocs, PI) and external collaborators (e.g. Amsterdam UMC, University of Amsterdam).
 Communicate research outcomes through papers and presentations at conferences,
workshops and other (scientific) gatherings.
 Assist in relevant teaching activities at universities, such as thesis supervision and assisting
in courses.