Software Engineer Decentralized and Confidential Learning on Structure Data

We are looking for candidates who satisfy the following requirements: an MSc degree with excellent results in Computer Science, preferably in distributed systems, theory, or related areas

• MSc degree in Computer Science
• 0-3 years of relevant experience.
• Experience in writing python and conducting scientific evaluations through experimentation
• Profound knowledge in deep machine learning algorithms and time series models
• Experience in designing and developing large scale distributed learning systems

• Duration of contract is 2 years Temporary
• A job of 36-40 hours per week.
• A salary based on Scale 10 of the CAO for Dutch Universities with a salary between €3546 - €5538 gross per month based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.

Federated learning (FL) is one of the emerging decentralized learning paradigm, which features on privacy protection by design. Under FL, machine learning models, e.g., LightGBM, and deep models, can be directly learned at the data premise, without centralized collecting data. In this research project, the main focus is on the tabular data and time series data due to its dominant presence in industries. The research objective of this PhD project is to derive scalable decentralized machine learning algorithms for tabular data. The key tasks of this project are: (i) designing privacy-preserving data exchanging strategies, (ii) deriving vertical and horizontal federated learning for tabular and time series data (iii) deriving generative models for tabular data, e.g., generative adversarial networks (iv) designing decentralized training framework for tabular and time series data synthesizer., Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. Challenge. Change. Impact! Faculty of Electrical Engineering, Mathematics and Computer Science The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment - which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.