Despite their impressive performance, machine learning systems remain largely unreliable in safety-, trust- and ethically sensitive domains. Recent discussions in several sub-fields of AI have reached the consensus of knowledge need in machines; few discussions, however, have touched upon the diagnosis of what knowledge is needed.
The aim of this PhD project is to develop human-in-the-loop methods and tools for the diagnosis of machine unknowns, a critical step towards reliable and trustworthy AI. We consider humans to be an indispensable means to understanding the knowns and unknowns of intelligent machines, through human interpretation of machine behavior and human creation of knowledge requirements. We also consider computational algorithms as a vital tool to assist humans in knowledge reasoning at scale, under uncertainty. The PhD candidate will, therefore, conduct both empirical and theoretical research, with primary activities characterized by the design, implementation, and analysis of human studies, computational algorithms, and human-in-the-loop systems.
Knowing machine unknowns is essential for both making AI –debugging the machine– and using AI –deciding when to trust the machine output– in any context. We envision the project to have both a tremendous scientific and practical impact, across all areas where AI and machine learning are applied.
The position is offered within the Web Information Systems (WIS) group at TU Delft. The WIS group concentrates its research on engineering and science of the Web, considering specifically the role of human-generated data in the engineering of Web-based information systems. The WIS group is an internationally leading research group with researchers and students advancing the state of the art in the following disciplines: large-scale data processing, information and knowledge extraction, information retrieval, human computation and crowdsourcing, human-computer interaction, and user modeling.
Requirements
The successful PhD candidate should:
- Have an MSc in Computer Science, or a closely related field;
- Have demonstrated competencies in one or more of these domains: Crowd Computing, Machine Learning, Natural Language Processing, Data Science, Human Computer Interaction;
- Have strong interest and/or experience conducting empirical and theoretical research;
- Be self-motivated and enjoy research;
- Be a team player;
- 6. Have good communication skills in Engligh.
Conditions of employment
TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible 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.
TU Delft (Delft University of Technology)
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 and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.
Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.
Additional information
For information about this vacancy and the selection procedure, please contact Dr. Jie Yang, Assistant Professor, email: J.Yang-3@tudelft.nl, with the subject [MachineUnknown].
Application procedure
Are you interested in this vacancy? Please apply before September 17, 2021 via the application button and upload the following in two pdf files:
- (pdf 1) 1-page Motivation letter and your CV;
- (pdf 2) a (part of your) M.Sc. thesis or a paper that you have written, in which you demonstrate your writing (and scientific) skills.
- Please highlight in your motivation letter and/or CV examples of projects and achievements that demonstrate your relevant competences.
- Please also include names and contact details of two references when applicable.
A pre-employment screening can be part of the selection procedure.
You can apply online. We will not process applications sent by email and/or post.
Acquisition in response to this vacancy is not appreciated.
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