The AI Department of the Donders Centre for Cognition (DCC), embedded in the Donders Institute for Brain, Cognition and Behaviour, and the School of Artificial Intelligence at Radboud University Nijmegen are looking for a researcher in reinforcement learning with an emphasis on safety and robustness, an interest in natural computing as well as in applications in neurotechnology and other domains such as robotics, healthcare and/or sustainability. You will be expected to perform top-quality research in (deep) reinforcement learning, actively contribute to the DBI2 consortium, interact and collaborate with other researchers and specialists in academia and/or industry, and be an inspiring member of our staff with excellent communication skills. You are also expected to engage with students through teaching and master projects not exceeding 20% of your time.

The Department of Psychology in the College of Arts and Sciences at American University invites applications for a full-time, tenure-track position at the rank of Assistant or Associate Professor beginning August 1, 2024. Rank will be dependent on experience and stature in the field. Depending on qualifications, the appointee to this position may be recommended for tenure at the time of hiring. In addition to scholarship and teaching, responsibilities will include participation in department, school and university activities. We welcome applications from candidates engaged in high-quality research in Cognitive or Social Psychology. The University has areas of strategic focus for research in Data Science and Analytics, Health, Security, Social Equity, and Sustainability. Priority will be given to outstanding researchers who can contribute meaningfully to one or more of these areas.

The Department of Computer Science in the College of Arts and Sciences at American University invites applications for a full-time, open-rank, tenure-line position beginning August 1, 2024. Applicants should have a PhD or an anticipated PhD completion by August 2024 in Computer Science or related fields. Depending on experience and qualification, the appointee to this position may be recommended for tenure at the time of hiring. Candidates can apply at the assistant, associate, or full professor level and we welcome applications from both academic and nonacademic organizations. We are looking for candidates who are excited at the prospect of joining a growing department where they will be able to make their mark. Preference will be given to candidates with a record of high-quality scholarship. For candidates applying at the associate or full professor level, a record of external funding is also expected. The committee will consider candidates engaged in high-quality research in any area of Computer Science related to Artificial Intelligence (E.g., Natural Language Processing, Machine Learning, Network Analysis, Information Visualization), Theoretical Computer Science (Computational Theory, Graph Theory, Algorithms), Cybersecurity, and other traditional areas of Computer Science (E.g., Software Engineering, Database Systems, Graphics, etc.). The University has areas of strategic focus for research in Data Science and Analytics, Health, Security, Social Equity, and Sustainability. Applicants from historically underrepresented minority and identity groups are strongly encouraged to apply. In addition to scholarship and teaching, responsibilities will include participation in department, school, and university service activities. Attention to Diversity, Equity and Inclusion (DEI) in all activities within the academic environment are expected.

The Department of Computer Science in the College of Arts and Sciences at American University invites applications for a full-time, open-rank, tenure-line position beginning August 1, 2024. Applicants should have a PhD or an anticipated PhD completion by August 2024 in Computer Science or related fields. Depending on experience and qualification, the appointee to this position may be recommended for tenure at the time of hiring. Candidates can apply at the assistant, associate, or full professor level and we welcome applications from both academic and nonacademic organizations. We are looking for candidates who are excited at the prospect of joining a growing department where they will be able to make their mark. Preference will be given to candidates with a record of high-quality scholarship. For candidates applying at the associate or full professor level, a record of external funding is also expected. The committee will consider candidates engaged in high-quality research in any area of Computer Science related to Artificial Intelligence (E.g., Natural Language Processing, Machine Learning, Network Analysis, Information Visualization), Theoretical Computer Science (Computational Theory, Graph Theory, Algorithms), Cybersecurity, and other traditional areas of Computer Science (E.g., Software Engineering, Database Systems, Graphics, etc.). The University has areas of strategic focus for research in Data Science and Analytics, Health, Security, Social Equity, and Sustainability. Applicants from historically underrepresented minority and identity groups are strongly encouraged to apply. In addition to scholarship and teaching, responsibilities will include participation in department, school, and university service activities. Attention to Diversity, Equity and Inclusion (DEI) in all activities within the academic environment are expected.

Manchester: Postdoc in probabilistic machine learning and sustainability; collaboration with an outstanding sustainability team - Univ Manchester is top in the UK and Europe, and 3rd in the world in the QS World University Ranking for Sustainability. This position belongs to the European Lighthouse of AI for Sustainability ELIAS. Helsinki: Probabilistic modelling and Bayesian inference for Machine Learning, ML for drug design, synthetic biology and biodesign, with differential privacy, for personalized medicine, for next-generation distribution shifts, or for collaborative machine learning.

i) ELIAS - European Lighthouse of AI for Sustainability: Join the team in the Sustainable Materials Innovation Hub led by Mike Shaver and the Centre for AI Fundamentals to transform the interface between AI and sustainability. The role involves using sustainability inputs to direct outcomes. ii) UKRI Turing AI World-Leading Fellowship: The role involves developing new principles and methods for Advanced User Modelling, sequential decision making, and Automatic Experimental Design, with and without a Human-in-the-Loop. iii) UKRI AI hub in Generative Models: The role involves developing principles and tools for generative models technology. iv) PhD student positions in the UKRI AI CDT in Decision Making for Complex Systems: Projects include 'Human-in-the-loop generative models for experimental design' and 'Learning theory and methods for novel types of distributional shifts'.

Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, I argue that these five challenges share a common cause: insufficient investment of resources into the typical psychology study. I further suggest that big team science can help address these challenges by allowing researchers to pool their resources to efficiently and drastically increase the amount of resources available for a single study. However, the current incentives, infrastructure, and institutions in academic science have all developed under the assumption that science is conducted by solo Principal Investigators and their dependent trainees. These barriers must be overcome if big team science is to be sustainable. Big team science likely also carries unique risks, such as the potential for big team science institutions to monopolize power, become overly conservative, make mistakes at a grand scale, or fail entirely due to mismanagement and a lack of financial sustainability. I illustrate the promise, barriers, and risks of big team science with the experiences of the Psychological Science Accelerator, a global research network of over 1400 members from 70+ countries.

Cement is the main binding agent in concrete, literally gluing together rocks and sand into the most-used synthetic material on Earth. However, cement production is responsible for significant amounts of man- made greenhouse gases—in fact if the cement industry were a country, it would be the third largest emitter in the world. Alternatives to the current, environmentally harmful cement production process are not available essentially because the gaps in fundamental understanding hamper the development of smarter and more sustainable solutions. The ultimate challenge is to link the chemical composition of cement grains to the nanoscale physics of the cohesive forces that emerge when mixing cement with water. Cement nanoscale cohesion originates from the electrostatics of ions accumulated in a water-based solution between like-charged surfaces but it is not captured by existing theories because of the nature of the ions involved and the high surface charges. Surprisingly enough, this is also the case for unexplained cohesion in a range of colloidal and biological matter. About one century after the early studies of cement hydration, we have quantitatively solved this notoriously hard problem and discovered how cement cohesion develops during hydration. I will discuss how 3D numerical simulations that feature a simple but molecular description of ions and water, together with an analytical theory that goes beyond the traditional continuum approximations, helped us demonstrate that the optimized interlocking of ion-water structures determine the net cohesive forces and their evolution. These findings open the path to scientifically grounded strategies of material design for cements and have implications for a much wider range of materials and systems where ionic water-based solutions feature both strong Coulombic and confinement effects, ranging from biological membranes to soils. Construction materials are central to our society and to our life as humans on this planet, but usually far removed from fundamental science. We can now start to understand how cement physical-chemistry determines performance, durability and sustainability.

The presentation will present the work of the Space Enabled Research Group at the MIT Media Lab. The mission of the Space Enabled Research Group is to advance justice in Earth’s complex systems using designs enabled by space. Our message is that six types of space technology are supporting societal needs, as defined by the United Nations Sustainable Development Goals. These six technologies include satellite earth observation, satellite communication, satellite positioning, microgravity research, technology transfer, and the infrastructure related to space research and education. While much good work has been done, barriers remain that limit the application of space technology as a tool for sustainable development. The Space Enabled Research Group works to increase the opportunities to apply space technology in support of the Sustainable Development Goals and to support space sustainability. Our research applies six methods, including design thinking, art, social science, complex systems, satellite engineering and data science. We pursue our work by collaborating with development leaders who represent multilateral organizations, national and local governments, non-profits and entrepreneurial firms to identify opportunities to apply space technology in their work. We strive to enable a more just future in which every community can easily and affordably apply space technology. The work toward our mission covers three themes: 1) Research to apply existing space technology to support the United Nations Sustainable Development Goals; 2) Research to design space systems that are accessible and sustainable; and 3) Research to study the relationship between technology design and justice. The presentation will give examples of research projects within each of these themes.