PhD Candidate in Causal Representation Learning and Fusion from Multiple Modalities

PhD Candidate in Causal Representation Learning and Fusion from Multiple Modalities

Published Deadline Location
3 Aug 15 Sep Amsterdam

Job description

Are you interested in applying ideas from causal inference, causal representation learning and information theory to learning causal relations from multimodal data, e.g., images, text, etc.? Are you excited about investigating fundamental questions and developing a unified principled framework, but also testing them empirically?

The Intelligent Data Engineering Lab (INDElab) at the University of Amsterdam (UvA) is seeking a PhD student in the area of causality, causal representation learning and multimodal data fusion. You will be working on a new fundamental research project, funded by the US Air Force Office of Scientific Research, aimed at creating foundational theory and methods for extracting and fusing causal knowledge from multiple modalities.

INDElab has both expertise in causality and causal representation learning, as well as data integration and extraction from multimodal data. In the lab, you will be working closely with Dr. Sara Magliacane and Prof. Paul Groth on this project.

What are you going to do

The focus of this PhD position is on extracting and fusing causal knowledge from multiple modalities. Most research in causality assumes that we have known causal variables and several samples. Instead, this PhD position focuses on causal representation learning, the problem of learning causal variables from multimodal data, including the case in which we might want to identify and fuse causal relations on single static entities in various modalities (e.g. the causal relations between two pieces of text, or two images).

You will be expected to:
  • develop a unified framework for causal representation learning from multimodal data, e.g. by identifying and fusing causal variables from single static entities in different modalities, e.g. two pieces of text, or two images, possibly by improving methods based on Minimum Description Length;
  • create a benchmark for causal data fusion based on real-world data;
  • publish at top tier conferences and journals;
  • collaborate with other researchers and project stakeholders;
  • assist in teaching and dissemination activities.

Specifications

University of Amsterdam (UvA)

Requirements

Your experience and profile:
  • A Master's degree in Machine Learning, Statistics, Computer Science, Mathematics, or a related field;
  • English fluency, both written and spoken;
  • Experience in programming and software development, in particular Python, R or C+, and possibly scientific computing or data science tools;
  • Passion for fundamental research and theoretical underpinnings of machine learning.
Candidates with a background in causal inference, representation learning and causal representation learning are preferred.

Conditions of employment

A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is as soon as possible. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary, based on 38 hours per week, ranges between € 2,541 in the first year to € 3,247 in the last year (scale P). This does not include the 8% holiday allowance and the 8,3% year-end allowance the UvA offers. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the '30% ruling', may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:
  • 232 holiday hours per year (based on fulltime);
  • Multiple courses to follow from our Teaching and Learning Centre;
  • A complete educational program for PhD students;
  • Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
  • 7 weeks birth leave (partner leave) with 100% salary;
  • Partly paid parental leave;
  • The possibility to set up a workplace at home;
  • A pension at ABP for which UvA pays two third part of the contribution;
  • The possibility to follow courses to learn Dutch;
  • Help with housing for a studio or small apartment when you're moving from abroad.
Are you curious to read more about our extensive package of secondary employment benefits, take a look here.

Employer

Faculty of Science

The University of Amsterdam is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 30,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.

The Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The mission of the Informatics Institute (IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.

The Intelligent Data Engineering Lab (INDELab) investigates intelligent systems that support people in their work with data and information from diverse sources. While most machine learning starts with an abundant set of fairly clean data, one of the lab's aims is to tackle machine learning problems in which the data is heterogeneous, noisy, missing or with few labels. You will be working closely with Dr. Sara Magliacane who specializes in causality-inspired machine learning and Prof. Paul Groth who works on automated knowledge base construction and data integration. The lab is strongly embedded in the larger UvA and Amsterdam artificial intelligence ecosystem with strong connections to multiple Innovation Centre for AI (ICAI) labs and the UvA's Data Science Centre. INDELab values practice-informed and interdisciplinary research and outreach.

Want to know more about our organisation? Read more about working at the University of Amsterdam.

Any questions

Do you have any questions or do you require additional information? Please contact:

Specifications

  • PhD
  • Natural sciences
  • max. 38 hours per week
  • €2541—€3247 per month
  • University graduate
  • 9999

Employer

University of Amsterdam (UvA)

Learn more about this employer

Location

Science Park 904, 1098XH, Amsterdam

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Application procedure

If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the button below. We will accept applications until and including 15 September 2022.

Applications should include the following information (all files besides your cv should be submitted in one single pdf file):
  • A letter of motivation, including a description of your research interests and an explanation for why you are applying for this position (at most two pages);
  • A CV, including a list of publications;
  • A list of all Master-level modules you have taken, with an official transcript of grades;
  • A link to a writing sample available online, such as a Master's thesis, a term paper, or a publication (in case of joint authorship, please clearly indicate your own contribution);
  • The names, affiliations, and email addresses of two or (at most) three people we can act as references for you (please do not include any reference letters in your application).
Please make sure to provide ALL requested documents mentioned above.
You can use the CV field to upload your resume as a separate pdf document. Use the Cover Letter field to upload the other requested documents, including the motivation letter, as one single pdf file.

Only complete applications received within the response period via the link below will be considered.

We will select a small number of candidates for the interviews by 30 September 2022. The interviews will be held early October 2022.

Application procedure

Application procedure

If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the button below. We will accept applications until and including 15 September 2022.

Applications should include the following information (all files besides your cv should be submitted in one single pdf file):
  • A letter of motivation, including a description of your research interests and an explanation for why you are applying for this position (at most two pages);
  • A CV, including a list of publications;
  • A list of all Master-level modules you have taken, with an official transcript of grades;
  • A link to a writing sample available online, such as a Master's thesis, a term paper, or a publication (in case of joint authorship, please clearly indicate your own contribution);
  • The names, affiliations, and email addresses of two or (at most) three people we can act as references for you (please do not include any reference letters in your application).
Please make sure to provide ALL requested documents mentioned above.
You can use the CV field to upload your resume as a separate pdf document. Use the Cover Letter field to upload the other requested documents, including the motivation letter, as one single pdf file.

Only complete applications received within the response period via the link below will be considered.

We will select a small number of candidates for the interviews by 30 September 2022. The interviews will be held early October 2022.

Make sure to apply no later than 15 Sep 2022 23:59 (Europe/Amsterdam).