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Privacy statement for job applicants to TU Delft

The privacy of job applicants is of great importance to Delft University of Technology (TU Delft). This privacy statement for job applicants explains how we deal with your personal data. This privacy statement relates to all processing of data done by TU Delft within the framework of the job selection procedure. Who is responsible for your data? Delft University of Technology, with its registered address at Mekelweg 5, 2628 CB Delft, is responsible for the processing of your data. The Data Protection Officer monitors the application of, and compliance with, the General Data Protection Regulation (GDPR). You can reach TU Delft's Data Protection Officer at privacy-tud@tudelft.nl . What personal data do we process? TU Delft processes the data provided by you regarding your job application. Your data might also be provided by a recruitment agency and processed by us. In addition to this, we also keep a record of the evaluation of your suitability for the vacancy you have applied for. In some selection procedures an assessment, internet search and/or, in the last phase of the selection, a pre-employment screening (background check) will be conducted. The results of these checks are recorded alongside your other data by TU Delft. Purpose for which we process your data TU Delft collects and processes the data of applicants who wish to indicate their interest in a position at TU Delft. The personal data are used to assess the candidate's suitability for the position in question, but are also used, for example, to invite a job applicant for an interview. In addition, the data are used to allow the recruitment and selection process to proceed in a responsible, efficient and effective manner as possible and to allow us to monitor and optimise this process. We do this, for example, by generating reports. The reports and any related recommendations can never be traced to an individual. Basis on which we process your data Your data are necessary for us to be able to consider whether you are suitable for the available vacancy, with the objective (in the event that you are suitable) of concluding an employment contract. We need to process your data in order to take steps at your request prior to entering into a contract (of employment) (GDPR Article 6(1)(b)). Without your data we cannot deal with your job application. If an application procedure ends without it leading to a contract of employment, you may indicate during the selection that we may retain your data (for a year at the longest) for future vacancies, for example, and your permission will then be the legitimate ground for processing your data. Who may inspect my data? Employees of TU Delft, and in some cases selected external parties, involved in the recruitment and selection for the vacancy in question you are responding to, may inspect your data. Besides this, only authorised controllers of the recruitment system have access to the data within TU Delft. TU Delft may share your data with companies who help us with the selection of applicants, for example recruitment and selection agencies and employment agencies. TU Delft may also share your data with suppliers of assessments, for example for the purpose of performing a personality test. If we work with an external party, we will always ask you for permission to share your data with the party in question. Where is the data stored? Lumesse BV, with its registered address in Leiden, was selected as supplier of the software package for this process, in accordance with European Tendering regulations. The choice of this supplier means that the data are no longer stored at TU Delft but on the supplier's systems. The contractual agreements made with Lumesse BV. are in total compliance with the General Data Protection Regulation (GDPR), the latest privacy legislation. Lumesse uses Amazon Web Services Inc. (Amazon) services to store the data. Contractual agreements have been made with Amazon to completely safeguard the privacy and security of information. The encrypted data is kept on servers belonging to Amazon in Frankfurt am Main (Germany), in a secure and ISO-certified data centre, which means that they are located in the European Union. Who has access to the data? Amazon is unable to access the data. As the software operating party, Lumesse does have access to the data. A processing agreement has been made between TU Delft and Lumesse in accordance with statutory privacy requirements. Within TU Delft, only authorised ICT administrators have access to the data. Retention period Our retention period is four weeks from the end of the selection procedure per applicant. This term is necessary for us to be able to complete the administrative procedures involved and, in the event of cancellation, to contact other applicants. During the selection process you may indicate that we may only retain your data in our portfolio for use regarding other vacancies for a maximum of one year after submission of the application. If you have given permission but wish to retract this before the end of the retention period, please contact the HR Contact Centre at TU Delft at hrservices@tudelft.nl . Data security TU Delft makes use of a recruitment system to monitor the recruitment and selection process. Various methods such as firewalls (network/computer protection), intrusion detection software and security procedures and organisational measures are used to secure your data against loss, damage, unauthorised access and improper use. All data shared between yourself and the recruitment system are secured to ensure that others cannot read them. How can I exercise my privacy rights? If you apply for a job at TU Delft, you are entitled to: access to your data; rectification of your data, if these contain factual inaccuracies; erasure of your data; transfer of your data; restriction of the specific processing of your data; object to the processing of your data. Such a request may be submitted via privacy-tud@tudelft.nl . Is anything still unclear to you? If you have questions about the privacy statement, please contact us at privacy-tud@tudelft.nl . New | Privacystatement Recruitment & Selection Click here for the privacy statement effective 14 October 2024.

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New LDE trainee in D&I office

Keehan Akbari has started since the beginning of September as a new LDE trainee in the Diversity and Inclusion office. What motivated him to work for the D&I office, what does he expect to achieve during this traineeship? Read the short interview below! What motivated you to pursue your LDE traineeship in Diversity and Inclusion office of the TU Delft? I completed both bachelor's and master's degrees in Cultural Anthropology and Development Sociology at Leiden University. Within these studies, my main area of interest was in themes of inclusion and diversity. After being hired as a trainee for the LDE traineeship, and discovering that one of the possible assignments belonged to the Diversity and Inclusion office, my choice was quickly made. I saw this as an excellent opportunity to put the theories I learned during my studies into practice. What specific skills or experiences do you bring to the D&I office that will help promote inclusivity on campus? I am someone who likes to connect rather than polarize, taking into account the importance of different perspectives and stakeholders. I believe that this is how one can achieve the most in fostering diversity and inclusion. You need to get multiple parties on board to get the best results. What are your main goals as you begin your role here, and how do you hope to make an impact? An important goal for me this year is to get students more involved in diversity and inclusion at the university. One way I will try to accomplish this is by contributing to the creation of D&I student teams. By establishing a D&I student team for faculties, it will be possible to deal with diversity- and inclusion-related issues that apply and relate to the specific department. How do you plan to engage with different (student) communities within the university? Since I am new to TU Delft, the first thing I need to do is expand my network here. Therefore, I am currently busy exploring the university and getting to know various stakeholders. Moreover, I intend to be in close contact with various student and study organizations to explore together how to strengthen cooperation on diversity and inclusion. Welcome to the team Keehan and we wish you lots of success with your traineeship!

Researchers from TU Delft and Cambridge University collaborate on innovative methods to combat Climate Change

For over a year and a half, researchers from TU Delft and the Cambridge University Centre for Climate Repair have worked together on groundbreaking techniques to increase the reflectivity of clouds in the fight against global warming. During a two-day meeting, the teams are discussing their progress. Researchers at Cambridge are focusing on the technical development of a system that can spray seawater, releasing tiny salt crystals into the atmosphere to brighten the clouds. The team from TU Delft, led by Prof. Dr. Ir. Herman Russchenberg, scientific director of the TU Delft Climate Action Program and professor of Atmospheric Remote Sensing, is studying the physical effects of this technique. Prof. Russchenberg emphasizes the importance of this research: "We have now taken the first steps towards developing emergency measures against climate change. If it proves necessary, we must be prepared to implement these techniques. Ideally, we wouldn't need to use them, but it's important to investigate how they work now." Prof. Dr. Ir. Stefan Aarninkhof, dean of the Faculty of Civil Engineering and Geosciences, expresses pride in the team as the first results of this unique collaboration are becoming visible. If the researchers in Delft and Cambridge can demonstrate the potential of the concept, the first small-scale experiments will responsibly begin within a year. This research has been made possible thanks to the long-term support from the Refreeze the Arctic Foundation, founded by family of TU Delft alumnus Marc Salzer Levi . Such generous contributions enable innovative and high-impact research that addresses urgent global challenges like climate change. Large donations like these enable the pursuit of innovative, high-impact research that may not otherwise be feasible, demonstrating how our collective effort and investment in science can lead to real, transformative solutions for global challenges like climate change. Climate-Action Programme

How system safety can make Machine Learning systems safer in the public sector

Machine Learning (ML), a form of AI where patterns are discovered in large amounts of data, can be very useful. It is increasingly used, for example, in chatbot Chat GPT, facial recognition, or speech software. However, there are also concerns about the use of ML systems in the public sector. How do you prevent the system from, for example, discriminating or making large-scale mistakes with negative effects on citizens? Scientists at TU Delft, including Jeroen Delfos, investigated how lessons from system safety can contribute to making ML systems safer in the public sector. “Policymakers are busy devising measures to counter the negative effects of ML. Our research shows that they can rely much more on existing concepts and theories that have already proven their value in other sectors,” says Jeroen Delfos. Jeroen Delfos Learning from other sectors In their research, the scientists used concepts from system safety and systems theory to describe the challenges of using ML systems in the public sector. Delfos: “Concepts and tools from the system safety literature are already widely used to support safety in sectors such as aviation, for example by analysing accidents with system safety methods. However, this is not yet common practice in the field of AI and ML. By applying a system-theoretical perspective, we view safety not only as a result of how the technology works, but as the result of a complex set of technical, social, and organisational factors.” The researchers interviewed professionals from the public sector to see which factors are recognized and which are still underexposed. Bias There is room for improvement to make ML systems in the public sector safer. For example, bias in data is still often seen as a technical problem, while the origin of that bias may lie far outside the technical system. Delfos: “Consider, for instance, the registration of crime. In neighbourhoods where the police patrol more frequently, logically, more crime is recorded, which leads to these areas being overrepresented in crime statistics. An ML system trained to discover patterns in these statistics will replicate or even reinforce this bias. However, the problem lies in the method of recording, not in the ML system itself.” Reducing risks According to the researchers, policymakers and civil servants involved in the development of ML systems would do well to incorporate system safety concepts. For example, it is advisable to identify in advance what kinds of accidents one wants to prevent when designing an ML system. Another lesson from system safety, for instance in aviation, is that systems tend to become more risky over time in practice, because safety becomes subordinate to efficiency as long as no accidents occur. “It is therefore important that safety remains a recurring topic in evaluations and that safety requirements are enforced,” says Delfos. Read the research paper .