Postdoc on Privacy-Preserving Data Analysis

Utilizing data effectively will become even more in addressing major challenges confronting us as a societe. The quality and availability of training data significantly impact the accuracy of data analyses and machine learning tasks. Nonetheless, data is frequently isolated in silos due to privacy issues, legal constraints, or conflicting economic motives, hindering its potential.

This position is embedded in the SHARE project, that aims to explore possibilities for privacy-preserving data sharing and joint data analytics for healthcare data. Within the project, the candidate will research privacy enhancing technologies for collaborative data analytics and distributed machine learning with a specific focus on vertically partitioned datasets. Techniques such as secure multiparty-computation and differential privacy will be applied and evaluated. The assessmement of privacy attacks in this specific database setting is another aspect the candidate can explore.

Requirements:

• You are a highly motivated and enthusiastic researcher, aspiring to do world-class research and have real-world impact.
• You have a PhD degree with a strong publication record in computer science or similar.
• You are specialized in the domain of applied cryptography or machine learning; a solid background in both areas is of additional advantage.
• You are an independent and original thinker with a creative mindset and excellent analytical and communication skills.
• You are curious and interested in learning how things work and how to make them better.
• You have great team spirit and you are open to work in an internationally oriented and interdisciplinary environment.
• You are fluent in English.

Salary Benefits:

• You will be appointed for a period of maximum one year full-time within a very stimulating scientific environment. The university offers a dynamic ecosystem with enthusiastic colleagues.
• Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU);
• Gross salary between € 4.020,- and € 5.278,- per month depending on experience and qualifications.
• Excellent benefits including a holiday allowance of 8% of the gross annual salary, a year-end bonus of 8.3% and a solid pension scheme;
• The flexibility to work (partially) from home.
• Free access to sports facilities on campus.
• A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
• Excellent support for research and facilities for professional and personal development.
• We encourage a high degree of responsibility and independence, while collaborating with close colleagues, researchers and other university staff.
• We are also a family-friendly institution that offers parental leave (both paid and unpaid) and career support for partners.

40 hours per week

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