Netherlands Job Openings

TU Delft

PhD position Machine learning for Human Behaviors in Negotiations and Deliberations

Delft

September 10, 2024

Ph D position Machine learning for Human Behaviors in Negotiations and Deliberations
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Job description

Negotiations and deliberations involve understanding and managing interpersonal dynamics, relationships, motivations, and navigating conflicts. While there has been much existing research in building negotiating agents, there remains a gap to integrate situated understanding of human behaviors and how these could affect negotiation and deliberation outcomes. What could be perceived from people’s interaction and communication patterns as well as decision-making across the negotiation and deliberation process? One solution is to leverage information gathered pre- and post- interaction, as well as multimodal data during the interaction process. As a member of this project, you will do research in the pipeline of multimodal machine perception and decision-making from data collection, annotation, algorithm and model design, to evaluation. The team you would join is a multi-disciplinary team, in which everyone is encouraged to take initiatives and progress in the work is achieved by shared ownership.
This project is part of a larger Groeifond consortium (Oncode Accelerator) which focuses on drug development and cancer research. This project is part of a work package that researches negotiations and deliberations between stakeholders in research and potentially clinical settings. This project aims to develop novel frameworks and learning approaches that integrate human behavior modeling to support decision-making in real-life scenarios.
The successful applicant will develop computational methods to model human behaviors using multimodal data - video and audio (e.g., speech and paralinguistics data), and to generate insights and feedback for descision-making, specifically for negotiation and deliberations in real-life situated settings.
The candidate will be embedded within the larger Interactive Intelligence Group at the Intelligent Systems Department at the TU Delft Electrical Engineering, Mathematics, and Computer Science faculty. For information about Ph D at TU Delft, please visit https://www.tudelft.nl/onderwijs/opleidingen/phd

Requirements

We are looking for applicants who have or expect to receive a Master's degree before joining the project. Relevant topics include multimodal machine learning, affective computing, natural language processing, and reinforcement learning. Experience in some of the related fields is preferred: audio and speech processing, computer vision, machine learning, and pattern recognition. As this project is interdisciplinary, having general interests and affinity in human-computer interaction, social science, and psychology is recommended.
Doing a Ph D at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2872 per month in the first year to € 3670 in the fourth year. As a Ph D 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 a monthly work costs contribution. Flexible work schedules can be arranged.
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

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 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 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.
Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

Additional information

For more information about this vacancy, please contact Stephanie Tan, s.tan-1@tudelft.nl.

Application procedure

Interested applicants should upload an up-to-date curriculum vitae, degree transcripts, letter of application, and the names and the contact information (telephone number and email address) of two referees. The letter of application should summarise (1) why the applicant wants the position, (2) why the project is of interest to the applicant, (3) evidence of suitability for the job, and (4) what the applicant hopes to gain from the position.
Interested candidates are encouraged to apply as soon as possible and before October 29, 2024. For information about the application procedure, please contact Anita Hoogmoed, A.M.Hoogmoed@tudelft.nl
Applications will be reviewed on a rolling basis.
  • 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.
  • Please do not contact us for unsolicited services.

FACULTY/DEPARTMENT
Faculty of Electrical Engineering, Mathematics & Computer Science
JOB TYPE
Ph D
SCIENTIFIC FIELD
Engineering
HOURS PER WEEK
36-40
SALARY
see vacancy text
DESIRED LEVEL OF EDUCATION
University graduate
VACANCY NUMBER
TUD05721
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