Artificial Intelligence is used more and more in society, from healthcare to government decisions and recruitment.
Along with the rapid increase of AI adoption come increased concerns about the inherent shortcomings of such
technologies (e.g., robustness) and the social, and ethical implications. To create AI systems that can properly serve humans,
it is crucial to put humans at the centre of the process such that the outcome system behaves in a way that fits the values and
needs of people. This poses new challenges both to philosophical work on values and to (responsible) technological development.
What (ethical) requirements should these systems adhere to? What does such ‘adherence’ mean and how can we demonstrate and
validate claims regarding adherence? How to build AI systems that can be understood by humans and that can align their behaviour
with human values? Tackling these challenges requires bridging the gap between philosophy and computer science within AI Ethics.
TU Delft has world-leading expertise in the operationalization of AI Ethics and now looks to strengthen this by hiring two three-year post-docs, one in philosophy and one in computer science, that will be closely collaborating on topics within AI Ethics of their choice.
More details can be found in the vacancies description.
To apply or inqury, please contact Jie Yang: j.yang-3@tudelft.nl.
Summary: We are searching for a motivated postdoctoral researcher to lead the research and development of dataset discovery and data augmentation tools using ML techniques. You will be working alongside a team of excellent PhD & MSc students, and taking part in funding opportunities, in order to build a strong academic CV.
Details: Data-driven enterprises nowadays need to discover, combine and analyze data at the petabyte scale. Data discovery aims at finding a subset of relevant datasets from a data lake that can be combined together and enable deep insights to a given question. Dataset discovery is one of the most intensively discussed data management challenges for big data. The current approaches mostly search for datasets with similar attribute names or overlapping instance values, handling tabular data or hierarchical data that can be transformed into tabular data. The challenges include finding joinable tables or semantically related tables. As part of the Web Information Systems (WIS) section, the data management team at TU Delft is interested in tackling exciting challenges of supporting common data science tasks, such as finding additional data for training or validation, and feature engineering.
The candidate is expected to lead a team in order to develop a novel data discovery system that integrates human knowledge and analytical goals with dataset characteristics, metadata, and quality. The duties of the postdoctoral researcher include authoring top-tier conference papers, supervising master and PhD students, and design or development of open-source data discovery tools.
We are looking for a motivated candidate to join our data management group (Dr. Rihan Hai, Dr. Asterios Katsifodimos). You will be part of a very motivated and vibrant group of researchers. Following TU Delft’s multi-annual strategy 2022-2025, 'health' is now a core domain focus for our faculty and we support young researchers pursuing their next career goals.
Requirements
Conditions of employment Salary and benefits are in accordance with the Collective Labor Agreement for Dutch Universities. TU Delft offers a customizable compensation package, a discount on health insurance and sports memberships, and a monthly work costs contribution. Flexible and remote work schedules can be arranged.
For international applicants, we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. An International Children's Center offers childcare and there is an international primary school.
To apply, please contact Dr. Rihan Hai at R.Hai@tudelft.nl.
Summary: Join the frontier of technology with our PhD positions in Quantum Data Management. At the Web Information Systems Group of the Software Technology Department in collaboration with QuTech, we are at the forefront of blending quantum computing with data management. This emerging field promises revolutionary advancements, offering solutions to classical database problems and opening doors to capabilities beyond current systems.
Details: Research and develop theoretical foundations for applying quantum computing to classical data management problems. Design and prototype innovative software solutions. We are seeking a proactive, inventive candidate passionate about crafting new methodologies at the intersection of data management and quantum computing.
Details: Address the unique challenges of distributed data management in the era of quantum internet. This position is ideal for an independent, ambitious individual eager to explore the nexus of distributed database systems, quantum hardware, and quantum information.
Requirements:
To apply, please contact Dr. Rihan Hai at Dr. Rihan Hai.
Summary: we are searching for a motivated research software engineer to lead the development of dataset discovery, data augmentation, and data integration tools using ML techniques. You will be working alongside a team of excellent PhD & MSc students. You will build (or use your existing) experience in working with modern (Big) data and cluster management tools (e.g., Apache Flink, Spark, Valentine, Kubernetes).
This position is a unique and exciting challenge to help create a new ground-breaking technology. Your main goal will be to design and implement open-source software that handles large-scale data and improve Machine Learning pipelines.
To apply, please contact Dr. Asterios Katsifodimos.
We are searching for two self-motivated PhD students and one postdoctoral researcher.
We are building a novel programming and execution model for data-intensive cloud applications, guaranteeing consistency and scalability with minimal effort from programmers.
Towards this goal, we perform research on an intermediate representation (IR) for cloud applications, capable of capturing programmers’ intent while being amenable to parallelization and distribution. Under the hood lies Stateflow: a parallel, transactional FaaS system based on streaming dataflows, able to execute general cloud applications. We are now extending Stateflow with the ability to adapt at runtime and sustain low-latency at a high scale.
Apply if you like to work in the broad areas of distributed systems, Cloud computing, programming languages/compilers, and database systems.
To apply, please contact Dr. Asterios Katsifodimos.