Pedagogical University

(Fixed Term for 8 Months) Liverpool John Moores University (LJMU) is a distinctive, unique institution, rooted in the Liverpool City Region and with a global presence. Our students and staff, past, present, and future, are the beating heart of our city and can be found in every corner of every industry and community. We couldn’t exist anywhere else and have shaped the city in which we belong. Working with the people of Liverpool to improve lives and support communities is at the heart of why we were founded and why we exist today. The School of Biological and Environmental Sciences, within the Faculty of Health, Innovation, Technology and Science, seeks to appoint a Lecturer in Conservation. This is an exciting opportunity to join an enthusiastic team and play an important role in ensuring our students enjoy a fantastic student experience.  You will be expected to make broad contributions to the academic work of the School of Biological and Environmental Sciences, particularly in the area of conservation. Experience in zoo conservation would be beneficial as would the ability to assist on field trips. You will hold a PhD in the field of Conservation Biology, and have experience of teaching undergraduate students, ideally across all levels. This is a fixed term position for 8 months to cover maternity leave.  In return, we offer an excellent benefits package including generous annual leave entitlement, pension scheme, induction and development support as well as family-friendly policies. This is an exciting time to join the university as we deliver the LJMU Strategy 2030 and its vision of LJMU as an inclusive civic university transforming lives and futures, by placing students at the heart of everything we do. If you feel that this is the role you have been looking for and your skills and experience can make a real difference at LJMU, we look forward to hearing from you. LJMU is an equal opportunities employer and welcomes applicants from all backgrounds and communities irrespective of age, transgender status, disability, gender, sexual orientation, ethnicity and religion or belief. All our appointments are made on merit. Please note all of our vacancies will be closed to applications at midnight on the advertised closing date, unless otherwise stated.

As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in its research pursuits. This position is situated within the Centre for Immersification, dedicated to applied research in immersive technologies and bridging the gap between academia and industry. Research staff at the Centre have the opportunity to be equipped with applied research skill sets relevant to industry demands while working on innovative projects within the university. The primary responsibility of this role is to contribute to the design, development, and deployment of an advanced content moderation framework for immersive 3D virtual environments, such as Roblox and Minecraft. The research staff will play a key role in building and integrating of AI agents into gaming scenarios (e.g., gameplay, interactions, procedural content generation, dynamic narratives), and integrating a multimodal detection pipeline, ensuring real-time performance, scalability, and deployment readiness in alignment with the project’s research objectives. The successful candidate will work with a diverse team of faculty members, engineers, and industry partners, including renowned researchers at the College of Computing and Data Science (CCDS) at NTU. Technical skills, natural curiosity, versatility, and enthusiasm are highly desired traits that will enable success in this fast-paced environment. Key Responsibilities Manage the research project together with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Collaborate with the PI, Co-PIs and NTU team to design and develop a robust and scalable software system for autonomous agents navigating immersive 3D virtual environments (e.g., Roblox, Minecraft). Design and develop robust and scalable game agents to navigate and interact with immersive 3D virtual environments (e.g., Roblox, Minecraft). Integrate AI agents into gaming scenarios (e.g., gameplay, interactions, procedural content generation, dynamic narratives) Leverage fine-tuned Vision-Language Models (VLMs) for game scenario detection, supporting zero-shot reasoning and scene-graph inference. Ensure the system is deployment-ready by supporting benchmarking of inference speed, compute efficiency, and scalability with concurrent agents. Maintain high software engineering standards through rigorous testing, version control, clear documentation, and continuous improvement of development infrastructure (e.g., CI/CD, Docker, cloud-based services). Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations. Coordinate procurement and liaison with vendors/suppliers. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Job Requirements Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in computer vision techniques, transformer architectures, and multi-modal learning. Familiarity with reinforcement learning (RL) principles, curriculum learning strategies, and the challenges of real-time systems. Working knowledge of distributed systems and container technologies (e.g., Docker, Kubernetes). Communicate research findings and project progress effectively through demos, internal presentations, and contributions to external academic forums where appropriate. A genuine passion for developing AI agents for games. Roblox or Minecraft players are a strong advantage. Key Competencies Strong software development and debugging skills. Demonstrable experience with machine learning frameworks. Proficient in technical writing and system documentation. Self-directed learner with strong problem-solving and research capability.

The University of Vienna is a community of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their passion and determination? To strengthen our team, we are seeking a university assistant to develop advanced machine learning and artificial intelligence methods. University assistant predoctoral - PhD position in Probabilistic and Interactive Machine Learning 39 Faculty of Computer Science Startdate: 01.10.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.09.2030 Reference no.: 5376 Your personal sphere of influence: The working group “Probabilistic and Interactive Machine Learning” within the research group “Data Mining and Machine Learning” at the Faculty of Computer Science, led by Prof. Sebastian Tschiatschek, develops foundational methods in machine learning and artificial intelligence. We focus particularly on the areas of reinforcement learning, interactive learning, and deep probabilistic models. While modern reinforcement learning (RL) has achieved remarkable success, it remains limited when applied to complex, open-ended, or poorly defined environments. Two of the most critical bottlenecks in contemporary AI are sample inefficiency, often caused by the lack of intelligent, structured exploration, and the "reward engineering" problem, where designing an explicit scalar reward function that captures desired behavior is incredibly difficult or impossible. Furthermore, as AI systems are deployed in more complex environments, the challenges of AI alignment (ensuring systems behave according to human preferences) and constrained learning (adhering to strict safety, legal, or physical boundaries) become important. This position is dedicated to addressing these core challenges by advancing the frontiers of Inverse Reinforcement Learning (IRL), exploration, and safe/aligned AI.                       Your future tasks: You actively participate in research, teaching & administration, which means: You will contribute to academic research projects in the above-mentioned areas. You will work on scientific articles and publish your research results. You will participate in academic conferences to present your research. We expect you to conclude your dissertation agreement within 12 months. You will work on your dissertation and bring it to completion. You will take on teaching responsibilities as specified by the collective agreement. You will support the supervision of students’ projects and theses. You will undertake administrative duties in research, teaching, and university administration, and support the organization of workshops, conferences, and symposia. This is part of your personality: Completed Master's degree (or comparable degree) in computer science, data science, mathematics, communication engineering, or a related field (Applications from candidates close to completion are welcome. Employment can only begin once the Master´s degree has been awarded.) Excellent command of English Outstanding written and oral communication skills Strong ability to collaborate within research teams Perseverance and a proven ability to bring projects to reliable completion High motivation and commitment to scientific excellence Willingness to travel, including participation in national and international conferences Solid knowledge of machine learning and artificial intelligence (in particular in the areas of bandits and reinforcement learning) Strong programming skills, preferably in Python. Experience with deep learning frameworks such as Jax, PyTorch, or TensorFlow. Excellent analytical skills and strong interest in developing a deep understanding of algorithms and methods Cooperative, team-oriented, and proactive working style The following are also desirable: Experience with research methods in the field of machine learning and artificial intelligence, as well as scientific writing Excellent academic record, ideally with initial research results in the area of the position, documented by publications or manuscripts in preparation Experience in university teaching International experience What we offer: Work-life balance: Our employees enjoy flexible working hours and can partially work remotely.  Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment. Good public transport connections: Your workplace is easily accessible by public transport. Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Fair salary: The basic salary of EUR 3.776,10 (on a full-time basis) increases if we can credit professional experience. Tenure: The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration. It is that easy to apply: Academic curriculum vitae  Letter of motivation including your project ideas (and description of your teaching experience, if available) Abstract of Master´s Thesis Degree certificates Transcript of records List of publications, evidence of teaching experience (if available) If you have any questions, please contact: Sebastian Tschiatschek sebastian.tschiatschek@univie.ac.at We look forward to new personalities in our team! The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. University of Vienna. Space for personalities. Since 1365. Data protection ​Application deadline: 06/06/2026 Prae Doc