For the recently established Cluster of Excellence CoE Bilateral Artificial Intelligence (BILAI), funded by the Austrian Science Fund (FWF), we are looking for more than 50 PhD students and 10 Post-Doc researchers (m/f/d) to join our team at one of the six leading research institutions across Austria. In BILAI, major Austrian players in Artificial Intelligence (AI) are teaming up to work towards Broad AI. As opposed to Narrow AI, which is characterized by task-specific skills, Broad AI seeks to address a wide array of problems, rather than being limited to a single task or domain. To develop its foundations, BILAI employs a Bilateral AI approach, effectively combining sub-symbolic AI (neural networks and machine learning) with symbolic AI (logic, knowledge representation, and reasoning) in various ways. Harnessing the full potential of both symbolic and sub-symbolic approaches can open new avenues for AI, enhancing its ability to solve novel problems, adapt to diverse environments, improve reasoning skills, and increase efficiency in computation and data use. These key features enable a broad range of applications for Broad AI, from drug development and medicine to planning and scheduling, autonomous traffic management, and recommendation systems. Prioritizing fairness, transparency, and explainability, the development of Broad AI is crucial for addressing ethical concerns and ensuring a positive impact on society. The research team is committed to cross-disciplinary work in order to provide theory and models for future AI and deployment to applications.

Okinawa Institute of Science and Technology (OIST) has up to 10 open faculty positions in fields including life sciences and computational sciences. Each faculty member runs an independent research unit with internal funding including PhD students and postdoc/technical staff positions. A tenure-track faculty will have a tenure review within 6 years and a tenured faculty can renew research funding with reviews every 5 years till retirement at 70. OIST is an international, interdisciplinary graduate university without department boundaries. Education, research, and administration are run in English and no Japanese skills are required. A variety of supports for foreign researchers and family members are provided.

The Research Training Group 2853 “Neuroexplicit Models of Language, Vision, and Action” is looking for 12 PhD Students - Fall 2025. Neuroexplicit models combine neural and human-interpretable (“explicit”) models in order to overcome the limitations that each model class has separately. They include neurosymbolic models, which combine neural and symbolic models, but also e.g. combinations of neural and physics-based models. In the RTG, we will improve the state of the art in natural language processing (“Language”), computer vision (“Vision”), and planning and reinforcement learning (“Action”). We also develop novel machine learning techniques for neuroexplicit models (“Foundations”). Our overarching aim is to contribute to a better understanding of the cross-cutting design principles of effective neuroexplicit models through interdisciplinary collaboration. The RTG is scheduled to grow to a total of 24 PhD students by 2025. An excellent and international group of twelve PhD students and one postdoc have already joined the RTG. Through the inclusion of ~20 associated PhD students and postdocs funded from other sources, it will be one of the largest research centers on neuroexplicit or neurosymbolic models in the world. The RTG brings together researchers at Saarland University, the Max Planck Institute for Informatics, the Max Planck Institute for Software Systems, the CISPA Helmholtz Center for Information Security, and the German Research Center for Artificial Intelligence (DFKI). All of these institutions are collocated on the same campus in Saarbrücken, Germany. The positions will be funded for four years at the TV-L E13 100% pay scale. They are intended to start in September 2025, but could start a little earlier or later depending on the student’s availability.

Parkinson's disease (PD) is the second most present neurodegenerative disease in the world after Alzheimer's. It is due to the progressive and irreversible loss of dopaminergic neurons of the substantia nigra Pars Compacta. Alpha synuclein deposits and the appearance of Lewi bodies are systematically associated with it. PD is characterized by four cardinal motor symptoms: bradykinesia / akinesia, rigidity, postural instability and tremors at rest. These symptoms appear when 80% of the dopaminergic endings disappear in the striatum. According to Braak's theory, non-motor symptoms appear much earlier and this is particularly the case with anxiety, depression, anhedonia, and sleep disturbances. In 90 to 95% of cases, the causes of the appearance of the disease remain unknown, but polluting toxic molecules are incriminated more and more. In Africa, neurodegenerative diseases of the Parkinson's type are increasingly present and a parallel seems to exist between the increase in cases and the presence of toxic and polluting products such as metals. My Web conference will focus on this aspect, i.e. present experimental arguments which reinforce the hypothesis of the incrimination of these pollutants in the incidence of Parkinson's disease and / or Parkinsonism. Among the lines of research that we have developed in my laboratory in Rabat, Morocco, I have chosen this one knowing that many of our PhD students and IBRO Alumni are working or trying to develop scientific research on neurotoxicity in correlation with pathologies of the brain.