Recruitment
Doctoral Candidate (MSCA) in Ethics and Societal Value Mapping for LLMs
The doctoral candidate will focus on mapping societal values and assessing the impact of LLMs on vulnerable groups. This project involves conducting an extensive literature review, desktop research, interviews with key stakeholders, and a large-scale survey to identify how vulnerable populations are affected by LLMs. The research will directly contribute to the development of ethical principles for LLM value alignment and governance models. The successful candidate will be supervised by Prof. Christoph Lütge (TUM) and work closely with leading experts, including Assistant Professor Carlos Zednik (TU/e), and Professor Andrea Cavallaro (Idiap).
TU Munich
School of Social Sciences and Techology
Doctoral Candidate (MSCA) in Ethics for LLM use in Mental Health Context
The doctoral candidate will focus on incorporating high ethical and legal standards in the development of LLM-based tools for mental health purposes. This includes identifying legal and ethical shortcomings in existing AI mental health applications, such as AI Companions and chatbots, and developing standards to foster resilience rather than emotional dependence. The candidate will work under the supervision of Prof. Dr. Christoph Lütge (TUM), and closely with Associate Professor Nicole Lønfeldt (RegionH) and advisors from Fujitsu.
TU Munich
School of Social Sciences and Techology
Doctoral Candidate (MSCA)
The doctoral candidate will focus on working with children and adolescents to address LLMs in the context of use in 3 use cases: education, positive mental health, and online news consumption. The doctoral candidate will develop and apply a behavioural, experimental cognitive approach to explore the stated and revealed preferences of users regarding LLMs.In addition to the primary focus of this doctoral project, we are open to exploring other relevant projects that align with our broader research interests, particularly in the areas of ecological active learning. This encompasses investigating how individuals, especially children and adolescents, actively engage with their environment, learn from it, and adapt their cognitive strategies to real-world challenges. These interests could open up further interdisciplinary opportunities to study human-technology interaction, cognitive development, and behavioral responses in various contexts.
TU Munich
School of Social Sciences and Techology
Doctoral Candidate (MSCA) in Educational Sciences and Design of Tangible Tools for Learning About Ethical LLMs
The research conducted by the doctoral candidate will implement the education use-case by explaining LLMs to children and young people through tangible manipulatives and turning insights from empirical research to inform digital tools to plug into LLMs to increase explainability. The candidate will work in collaboration with an interdisciplinary team of leading experts in the field to design and test tangible learning environments for explaining LLMs to children and young people and assessment for capturing learning about value aligned LLMs. Applying mixed methods (with focus on qualitative) research methods and analytical techniques, the candidate will capture and analyse empirical evidence of learning outcomes and processes toward improved knowledge of learning about LLMs. The PhD candidate will be able to carry out a dissertation project within the use case of LLMs in education supervised by Prof. Dr. Anna Keune (TUM).
TU Munich
School of Social Sciences and Techology
Doctoral Candidate (MSCA) in Legal and Ethical Aspects of LLM-based Tools
The research conducted by the doctoral candidate is situated within the thematic context of LLM governance models to advance the legal and ethical aspects of LLM-based tools across three use cases: education, positive mental health, and online news consumption. The fellow candidate will work in collaboration with an interdisciplinary team to build ethical business models for LLMs, examine the LLMs’ regulatory landscape, and translate the lessons learned into legal recommendations, practical guidelines, and toolkits to ensure ethical, legal, and technical alignment in the three use cases. The PhD candidate will be able to carry out a dissertation project within the framework of LLMs governance supervised by Prof. Dr. Urs Gasser (TUM).
TU Munich
School of Social Sciences and Techology
Doctoral Candidate (MSCA) F/H/ in Aligned LLM Companions
The doctoral candidate will focus on personas and prompt templates for aligned LLM companions, investigating how to identify user personas and on how to craft LLM companions that align to values and preferences. The successful candidate will have the opportunity to work closely with leading experts in the field.
Idiap Research Institute
Switzerland
Doctoral Candidate (MSCA) F/H
The doctoral candidate will focus on the robustness of explanations via adversarial prompting, using adversarial refinement to robustify an LLM. The successful candidate will have the opportunity to work closely with leading experts in the field.
Idiap Research Institute
Switzerland
Doctoral Candidate (MSCA) in Child and Adolescent Mental Health Services
The doctoral candidate will be a part of the digital psychiatry research group that employs, develops, and tests machine learning techniques, wearables, and artificial intelligence tools in the context of research and practice of child and adolescent psychiatry. The group has a longstanding close collaboration with data scientists at the Technical University of Denmark. The group is currently working on automating evaluation of cognitive behaviour therapy for obsessive compulsive disorder, developing and testing an app-based intervention, and a national digital mental health platform.
Region Hovedstaden Psykiatri
Doctoral Candidate (MSCA) in Interdisciplinary LLM research
The AlignAI Doctoral Network aims to train doctoral candidates in the interdisciplinary Large Language Model (LLM) research field. It focuses on aligning these models with human values to ensure their development and deployment are ethically sound and socially beneficial. By integrating expertise from social sciences, humanities, and technical disciplines, the project will address critical issues such as explainability and fairness, ensuring LLMs contribute positively to education, mental health, and news consumption.
The doctoral candidate will focus on responsible data integration, and the successful candidate will have the opportunity to work closely with leading experts in the field.
Technion - Israel Institute of Technology
Doctoral Candidate (MSCA) in Building Human-Centered AI Tools for LLM Alignment in the Context of News
The doctoral candidate will investigate computational methods and build practical tools for value-aligned, LLM-based news generation and consumption. Research will range from the investigation of how LLMs can be used to responsibly generate news (in both forms and content) to how explainability techniques could be combined with LLMs in appropriate ways for diverse news audiences in support of their goals. Tools will be tested in real-life environments for news generation and consumption.
The successful candidate will be supervised by Prof. Daniel Gatica-Perez (EPFL) and work closely with other leading academics as well as professional news organizations in the alignAI consortium.
EPFL
Doctoral Candidate (MSCA) in Human-Centered Methods for LLM Alignment in the Context of News
The doctoral candidate will investigate, using mixed-methods approaches combining qualitative and computational approaches, research questions related to identifying values and emerging practices regarding the use of LLMs in the context of news, both for news creators and news audiences. The envisioned research ranges from studying the values promoted by news creators, to uncovering the level of personalization and algorithmic awareness expected by news audiences, and how they can be included in and supported by LLM technologies.
The successful candidate will be supervised by Prof. Daniel Gatica-Perez (EPFL) and work closely with other leading academics as well as professional news organizations in the alignAI consortium.
EPFL
Doctoral Candidate (MSCA) in Philosophical Contraints on the Explainability and Fairness of LLMs
The doctoral candidate in this position will develop a philosophical framework to ensure and evaluate the explainability and fairness of Large Language Models. This framework will center on conceptual and theoretical tools with which to understand, systematize, and evaluate formal and computational methods from AI that help explain the behavior of state-of-the-art LLMs, and that help align such systems with human values generally and fairness-related values specifically. Depending on the interest and expertise of the candidate, these tools might be designed to attribute conceptual or cognitive capacities to artificial neural networks on the basis of their learned representations, to apply benchmarks or statistical measures to evaluate the fairness and toxicity of their generated content, and/or to evaluate the success of probing and intervention techniques to manipulate their behaviors.
The doctoral candidate will be supervised by Carlos Zednik and Lambèr Royakkers, and will be embedded within the Philosophy & Ethics group, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology (TU/e). Additional supervision will be provided within the AlignAI doctoral network by Andrea Cavallaro (EPFL) and Christoph Lütge (TU München).
Eindhoven University of Technology (TU/e)
Doctoral Candidate (MSCA) on Developing a User-centric AI Evaluation Framework for LLMs
The doctoral candidate in this position will develop and test a user-centric AI evaluation framework that triangulates subjective metrics such as perceived transparency, understandability, fairness and cognitive explainability (mental models), with objective measures of explanation and model quality. Quantitative and qualitative user studies will be developed iteratively throughout the project within the three use cases of the AlignAI consortium: Education, positive health and online news consumption. The candidate will support the validation of AI tools developed by other candidates within alignAI consortium and final validation step with user groups towards the end of the project.
The doctoral candidate will be supervised by associate Professor Martijn Willemsen and professor Chris Snijders and embedded within the Human-Technology Interaction group, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology (TU/e). Additional supervision will be provided within the AlignAI doctoral network by Assistant Professor Sneha Das (Computer Science, DTU) and Professor Daniel Gatica- Perez (Digital Humanities,EPFL).
Eindhoven University of Technology (TU/e)
Doctoral Candidate (MSCA) in Key Enabling Methodologies (KEMs) for Harmonising LLMs with Societal Values
The doctoral candidate will need to apply methods from design-led and qualitative research to philosophy of technology, human-computer interaction, computer science, science and technology studies, innovation management, and/or related disciplines. They will also need to develop an appreciation of contemporary LLM applications as complex socio-technical systems. Thus, the ideal candidate will have an interdisciplinary background that spans several of the aforementioned disciplines, and that demonstrates a clear interest in AI technology and its societal impact. At the same time, the candidate will have the necessary language, communication, and analytic skills to produce research of publishable quality.
The doctoral candidate will be supervised by Prof. Stephan Wensveen and Dr. Jesse Benjamin embedded within the cluster Designing with Intelligence, Department of Industrial Design, Eindhoven University of Technology (TU/e). Additional supervision will be provided within the AlignAI doctoral network by Prof. Daniel Gatica Perez (Digital Humanities, EPFL) and Professor Azzurra Ruggeri (Psychology, TU München).
Eindhoven University of Technology (TU/e)
Doctoral Candidate (MSCA) in Generative AI in Design Education
The doctoral candidate will need to apply methods from design-led and qualitative research to philosophy of technology, philosophy of education, and/or related disciplines. They will also need to learn about contemporary LLM applications not only in education, but also how their effects across mental health concerns and online news consumption shapes education needs. Thus, the ideal candidate will have an interdisciplinary background that spans several of the aforementioned disciplines, and that demonstrates a clear interest in AI technology and its societal impact. At the same time, the candidate will have the necessary language, communication, and analytic skills to produce research of publishable quality.
The doctoral candidate will be supervised by Prof. Stephan Wensveen and embedded within the cluster Designing with Intelligence, Department of Industrial Design, Eindhoven University of Technology (TU/e). Additional supervision will be provided within the AlignAI doctoral network by Jürgen Neises (Fujitsu) and Prof. Anna Keune (TU München).
Eindhoven University of Technology (TU/e)
Doctoral Candidate (MSCA) in Computer Science and Statistics for LLMs and GenAI in Mental Health Context
The doctoral candidate will focus on the Positive Mental Health use case, towards the development of AI mental health assistants for mental health workers, patients, and patients’ caregivers that summarizes medical journal entries, takes journal notes, and spares on diagnostic criteria and treatment planning. Furthermore, the candidate will develop frameworks for the evaluation and auditing of LLMs. The student will work at DTU with assistant Prof. Sneha Das (principal supervisor) and Prof. Line Clemmensen (co-supervisor) and closely with senior researcher Nicole Lønfeldt (the Child and Adolescent Mental Health Services (CAMHS) in the Capital Region of Denmark) and advisors from Datacation.
Technical University of Denmark
Doctoral Candidate (MSCA) in Computer Science and Statistics for LLMs and GenAI in Education
The doctoral candidate will work towards LLMs and GenAI tools for learning technologies and education, with value alignment on explainability and fairness and focus on user-in-the-loop approaches. Furthermore, the candidate will develop frameworks for the evaluation and auditing of LLMs within this context. The student will work at DTU with assistant prof. Sneha Das (principal supervisor) and Prof. Line Clemmensen (co-supervisor) and closely with Prof. Stephan Wensveen (TU/e) and advisors from Datacation.