PRR Project

Summary

This position targets one Early Career Researcher (ECR) in “Artificial Intelligence for Scientific Discovery”, with a strong background in Artificial Intelligence (AI) and Knowledge-based systems, and experience in areas that include machine learning, natural language processing, computer vision, explainability or other relevant areas of AI research. Candidates should have familiarity with scientific applications of AI across different scientific fields (e.g., biology, biomedical science, chemistry, physics, environmental science), working with large-scale, heterogeneous scientific datasets, and conducting user studies to understand how scientists and AI can collaborate.Suitable candidates are expected to conduct high-profile scientific research to advance the state of the art in AI for scientific discovery with a focus on developing AI algorithms and techniques based on a sound theoretical approach that help scientists generate hypotheses, design experiments, collect and interpret large datasets, and gain insights that might not have been possible using traditional scientific methods alone.Candidates should have a strong publication record in top-tier conferences and journals. Experience in writing grant proposals to secure funding for future research initiatives will be much valued. They should be able to present research findings effectively in oral and written form and actively participate in international fora in the field, such as renowned conferences, high-tier workshops or thematic schools.The successful candidate will be expected to mentor and supervise MSc and PhD students, in alignment with LASIGE’s core objectives of developing a scientific culture that promotes excellence, while maintaining a healthy research environment.Moreover, they will be responsible for teaching advanced courses in Artificial Intelligence, Machine Learning and Artificial Intelligence for Science. Previous teaching experience will be valued, in particular, experience in designing activities that highlight the application of AI to scientific challenges and seamlessly integrating novel scientific developments in second-cycle curricula. The researcher will also be expected to contribute to teaching students across different scientific domains, and in training scientists in designing, implementing and applying AI in scientific research.AI is increasingly pervasive in scientific research, creating the need for a deeper understanding of the broader implications of its use, both in terms of scientific validity, utility and societal impact. Addressing challenges in reproducibility, out-of-distribution generalisation, incorporation/extraction of scientific knowledge into/from models, scalability and handling uncertainty are at the forefront of research in this area, but ethical, safety and security concerns, especially in what regards dual use cannot be ignored. A critical aspect that underlies the success of AI for scientific discovery is in supporting interpretability and explainability, to ensure that the knowledge created by AI approaches becomes fully available to scientists and advances human knowledge of complex natural phenomena.