Postdoctoral Researcher Buddhist Ethics for a Systemic Answer to the Attention Economy

Short introduction
Are you interested in exploring systemic solutions to the challenges posed by the attention economy? Do you have a scholarly interest in Buddhist ethics? Are you enthusiastic about engaging in collaborative research within a large network of philosophers of technology as part of the ESDiT project?

In this postdoctoral position:

• You will apply Buddhist ethics to critically examine and reinterpret the concept of attention, viewing it as a systemic, embedded, and political phenomenon.
• You will actively participate in ongoing societal and political debates surrounding the attention economy, both to contribute meaningfully to these discussions and potentially to gather empirical insights for your research.
• You will leverage your reconceptualization of attention to generate broader insights into how concepts related to disruptive technologies can be reimagined more generally.

Job Description
There is an exponential growth of critiques to the attention economy (the socio-technical system - combining users, organisations such as tech-companies and governments, devices and AI-systems, laws, regulations and business models, and more - that uses attention of individuals and groups to produce outputs - such as interactive software, profit, and influence).

This project starts from the hypothesis that many current critiques of the attention economy are insightful, but lack transformative strength because they frame attention as an individual, neutral and a-political technical concept with an isolated cognitive function, detached from ethics and neutral to political structures.

This project will reinterpret attention as a systemic concept in relation to socially disruptive technologies. It will develop a more ecology-focussed approach by developing an “ecology of attending” as a moral, political and social orientation leading towards action committed to the alleviation of avoidable suffering rather than to personal gratification.

It will use Buddhist philosophy and ethics to do so. Attention in Buddhism is a practice that cannot be considered as neutral or in isolation, but needs to be seen as embedded. It is part of an 'ecology', a system of moral and epistemic meaning that emerges from its natural objects, individual beings, and collective constituents. To this end, Buddhist philosophies offer numerous valuable insights to grasp the ethical implications of attention economy. For example, the core teachings of the four noble truths and the eightfold path outline a practical path towards ending suffering. Several Sutta’s present attention and mindfulness (manasikārā and sati) to describe that it is impossible to conceive of right attention, let alone practice it, without referring to ethical and wisdom cultivation.

Studying how one can re-conceptualise the notion of attention, may also allow to draw insights into the broader question, how ethical concepts can and should be re-evaluated from a non-Western perspective. The project will therefore extrapolate insights to other ethical theories and other socially disruptive technologies (SDT) in the ESDiT project.

This research position will focus on the following two research questions:

1. How can insights from Buddhist philosophies help us to reconceptualize attention as a systemic, embedded, and political mechanism in SDTs that fosters an ecology of attending?
2. What can this one particular study of attention add to the general insights of systemic-focused reconceptualizations?

As a postdoctoral researcher, you will

• develop an ethical theory on attention using Buddhist intellectual resources;
• engage actively in societal discussion and reaching out to policy makers and companies; and
• contribute to two ESDiT research lines (intercultural philosophy and conceptual disruption).

You will achieve this goal in a team, together with Gunter Bombaerts, Wijnand IJsselsteijn, Andreas Spahn (TU Eindhoven, the Netherlands) and Elena Ziliotti (TU Delft, the Netherlands).

Job Requirements

• Motivated researcher, with a PhD (obtained or defense planned in the near future) in research on Philosophy or Ethics or a comparable domain.
• Ability to conduct high quality academic research, reflected in demonstrable outputs.
• Motivated to actively engage in public and political debates on your topic.
• Good academic writing skills and excellent (written and verbal) proficiency in English, good communication and coordination skills.
• A team player who enjoys working in a dynamic, interdisciplinary team.
• A proven ability to manage complex projects to completion on schedule.
• Being a practitioner (meditation, …) yourself is not a must, but is certainly seen as a strength.

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for 3 years. An alternative schedule (for example: 4 years 75%) is possible.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (min. € 3,378 max. € 5,331).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs on general skills, didactics and topics related to research and valorization.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs.
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Gunter Bombaerts (g.bombaerts@tue.nl) for general questions about the project and the content.

Visit our website for more information about the application process or the conditions of employment. You can also contact our HR Advisor (hradvice.ieis@tue.nl).

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application using the apply-button. The application should include a:

• Cover letter in which you describe your motivation, qualifications for the position, and your first ideas about what you would like to do in this project.
• Curriculum vitae, including a list of your publications and the contact information of three references.
• List of self-selected ‘best publications’.

We look forward to receiving your application. We will start screening applications after Monday June 23rd 2025 and plan to have interviews in the week of July 7-11, 2025. The vacancy will remain open until the position is filled.

PhD on Multi-modal Open-Source Foundation Models

Introduction
Join a groundbreaking project to develop next-generation, open-source multi-modal foundation models. Collaborate with top research labs and experts to create transparent, efficient, high-performing models with novel capabilities that democratize access to AI. Apply now!

Job Description
We are seeking a highly motivated PhD student to join our research team in an ambitious 4-year project on next-generation multimodal, open-source foundation models. You’ll be part of an excellent team of scientists, covering the full spectrum from model development to evaluation and real-world use cases.

Snapshot
Artificial Intelligence is reshaping our world. Now you get to shape AI. This large and ambitious project aims to develop advanced, multimodal, open source foundation models based on solid research on model architecture, data quality, scaling, generalizability, finetuning, and safety. The focus is on multimodality aspects, including tabular and time series data, as well as efficient model finetuning. It combines the unique expertise of leading AI companies and top academic labs. This will be an inclusive, community-driven project designed to and foster a new wave of innovation and scientific advancement.

The team
The Automated Machine Learning team at TU Eindhoven focusses on cutting-edge research to advance the capabilities of machine learning models, while also democratizing AI and leveraging it to help humanity. We are a team of scientists and engineers who aim to deeply understand, explain, and build AI systems that learn continually and automatically assemble themselves to learn faster and better. In addition to producing highly-cited research published at top academic venues, we build models and systems that are widely used by people every day. Learn more about us here: https://openml-labs.github.io. This work is part of a large and talented team with world-class labs and experts across Europe, supported by well-known companies with advanced knowledge of LLM development.

The role
We are looking for an exceptional researcher with a real passion for AI, with a deep understanding of the latest developments and eager to explore new avenues of research. In this role, you will design and build cutting-edge methods that will shape the future of foundation models, and that will be deployed in real-world applications. We appreciate a strong empirical and theoretical understanding of deep learning and generative AI.

Key Research Areas:

• Multi-modal foundational model training and in-depth evaluation.
• Transfer learning and model adaptation, especially parameter-efficient finetuning.
• Model finetuning, including human-aligned finetuning (e.g. RLHF), grounded finetuning, and test-time training.
• Model evaluation, especially for new capabilities, generalization performance and model safety.
• Multi-model applications in new modalities including tabular and stream data, also in industry settings.

This research will be performed under the supervision of professor Joaquin Vanschoren, in collaboration with several key European research labs and industrial partners.

Job Requirements

• A master’s degree (or an equivalent university degree) in Computer Science or a related field.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Experience in programming and empirical analysis in Deep Learning (e.g. in Python, PyTorch).
• Excellent problem-solving skills and ability to work independently and collaboratively.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Conditions of Employment

• A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 2,901 max. € 3,707).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Joaquin Vanschoren, Associate Professor, j.vanschoren@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact Anna Vettoruzzo, Postdoctoral researcher, a.vettoruzzo@tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Postdoctoral Researcher Buddhist Ethics for a Systemic Answer to the Attention Economy

There is an exponential growth of critiques to the attention economy (the socio-technical system - combining users, organisations such as tech-companies and governments, devices and AI-systems, laws, regulations and business models, and more - that uses attention of individuals and groups to produce outputs - such as interactive software, profit, and influence).

This project starts from the hypothesis that many current critiques of the attention economy are insightful, but lack transformative strength because they frame attention as an individual, neutral and a-political technical concept with an isolated cognitive function, detached from ethics and neutral to political structures.

This project will reinterpret attention as a systemic concept in relation to socially disruptive technologies. It will develop a more ecology-focussed approach by developing an “ecology of attending” as a moral, political and social orientation leading towards action committed to the alleviation of avoidable suffering rather than to personal gratification.

It will use Buddhist philosophy and ethics to do so. Attention in Buddhism is a practice that cannot be considered as neutral or in isolation, but needs to be seen as embedded. It is part of an 'ecology', a system of moral and epistemic meaning that emerges from its natural objects, individual beings, and collective constituents. To this end, Buddhist philosophies offer numerous valuable insights to grasp the ethical implications of attention economy. For example, the core teachings of the four noble truths and the eightfold path outline a practical path towards ending suffering. Several Sutta’s present attention and mindfulness (manasikārā and sati) to describe that it is impossible to conceive of right attention, let alone practice it, without referring to ethical and wisdom cultivation.

Studying how one can re-conceptualise the notion of attention, may also allow to draw insights into the broader question, how ethical concepts can and should be re-evaluated from a non-Western perspective. The project will therefore extrapolate insights to other ethical theories and other socially disruptive technologies (SDT) in the ESDiT project.

This research position will focus on the following two research questions:

1. How can insights from Buddhist philosophies help us to reconceptualize attention as a systemic, embedded, and political mechanism in SDTs that fosters an ecology of attending?
2. What can this one particular study of attention add to the general insights of systemic-focused reconceptualizations?

As a postdoctoral researcher, you will

• develop an ethical theory on attention using Buddhist intellectual resources;
• engage actively in societal discussion and reaching out to policy makers and companies; and
• contribute to two ESDiT research lines (intercultural philosophy and conceptual disruption).

You will achieve this goal in a team, together with Gunter Bombaerts, Wijnand IJsselsteijn, Andreas Spahn (TU Eindhoven, the Netherlands) and Elena Ziliotti (TU Delft, the Netherlands).

PhD on Multi-modal Open-Source Foundation Models

We are seeking a highly motivated PhD student to join our research team in an ambitious 4-year project on next-generation multimodal, open-source foundation models. You’ll be part of an excellent team of scientists, covering the full spectrum from model development to evaluation and real-world use cases.

Snapshot
Artificial Intelligence is reshaping our world. Now you get to shape AI. This large and ambitious project aims to develop advanced, multimodal, open source foundation models based on solid research on model architecture, data quality, scaling, generalizability, finetuning, and safety. The focus is on multimodality aspects, including tabular and time series data, as well as efficient model finetuning. It combines the unique expertise of leading AI companies and top academic labs. This will be an inclusive, community-driven project designed to and foster a new wave of innovation and scientific advancement.

The team
The Automated Machine Learning team at TU Eindhoven focusses on cutting-edge research to advance the capabilities of machine learning models, while also democratizing AI and leveraging it to help humanity. We are a team of scientists and engineers who aim to deeply understand, explain, and build AI systems that learn continually and automatically assemble themselves to learn faster and better. In addition to producing highly-cited research published at top academic venues, we build models and systems that are widely used by people every day. Learn more about us here: https://openml-labs.github.io. This work is part of a large and talented team with world-class labs and experts across Europe, supported by well-known companies with advanced knowledge of LLM development.

The role
We are looking for an exceptional researcher with a real passion for AI, with a deep understanding of the latest developments and eager to explore new avenues of research. In this role, you will design and build cutting-edge methods that will shape the future of foundation models, and that will be deployed in real-world applications. We appreciate a strong empirical and theoretical understanding of deep learning and generative AI.

Key Research Areas:

• Multi-modal foundational model training and in-depth evaluation.
• Transfer learning and model adaptation, especially parameter-efficient finetuning.
• Model finetuning, including human-aligned finetuning (e.g. RLHF), grounded finetuning, and test-time training.
• Model evaluation, especially for new capabilities, generalization performance and model safety.
• Multi-model applications in new modalities including tabular and stream data, also in industry settings.

This research will be performed under the supervision of professor Joaquin Vanschoren, in collaboration with several key European research labs and industrial partners.

PhD on AI for Safety-Critical Multi-modal Learning

Introduction
Are you eager to make a difference in the advancement of AI via reliable state-of-the-art deep learning models? This position will explore efficient multi-modal models for safety-critical applications based on robustness guarantees and explainable AI built on insight into learned representations.

Job Description
We are seeking a highly motivated PhD student to join our research team in an ambitious project at the intersection of Safe AI, Resource Constrained, and Multi-Modal Learning. The focus of this PhD is on developing novel state-of-the-art AI models for safety-critical applications in which resilience, autonomy, and intelligence are required.

The overarching goal of this project is to develop efficient, trustworthy AI models that have a robust understanding of their environment based on various data sources. For example, the model should be able to integrate camera, radar, and other sensor modalities. Particular attention will be paid to transformer- and post-transformer architectures, and how to adapt them to learn efficiently on resource-constrained hardware, for instance with transfer learning and quantization techniques.

A key challenge of this project will be to design novel transformer-based architectures and adaptation techniques that are both efficient and reliable. The latter will require you to investigate and ultimately control the latent representations of knowledge in the model. This can be tackled from the viewpoint of various areas of machine learning, such as disentanglement of features, out-of-distribution awareness, robustness to adversarial attacks, and explainability, including the development of formal robustness guarantees that provide insights into the fundamental characteristics of the model that contribute to its safety and reliability in real-world applications. You will also assist in the integration and experimental evaluation of these techniques. Explainability will play an important role here, ensuring that models validate their explanations and provide insight into their latent representations, identifying what the model deems relevant for its predictions.

An auxiliary goal of this PhD is to make the employed models resource-efficient, ensuring they can run effectively on embedded accelerators (e.g., TPUs, NPUs, FPGAs) in constrained environments. The research will explore techniques such as model compression and quantization to optimize AI models for real-time operation on embedded platforms.

Key Research Areas:

• Multi-modal perception (e.g., radar, LiDAR, camera fusion) for robust real-world understanding.
• Transformer-based and post-transformer architectures optimized for embedded accelerators.
• Latent representation of knowledge for novel situation awareness and uncertainty estimation.
• Uncertainty-aware AI: Developing models that can identify when they "don’t know" and communicate uncertainty in decision-making.
• Resource-efficient AI techniques, including compression, quantization, and low-power optimization.

This research has strong implications for autonomous robotics, industrial automation, and safety-critical AI applications, where models must react to unexpected situations and make trustworthy decisions with limited computational resources.

This research will be performed under the supervision of professors Joaquin Vanschoren, Vlado Menkowski, Mykola Pechenizkiy, and Sibylle Hess, in collaboration with several key industrial players in advanced semiconductors.

Job Requirements

• A master’s degree (or an equivalent university degree) in Computer Science or a related field.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Experience in programming and empirical analysis in Deep Learning (e.g. in Python, PyTorch).
• Excellent problem-solving skills and ability to work independently and collaboratively.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Conditions of Employment

• A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 2,901 max. € 3,707).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Joaquin Vanschoren, Associate Professor, j.vanschoren@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact Sibylle Hess, Assistant Professor, s.c.hess@tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.