Bohai University

The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research. We are ambitious and have a bold vision - shaping ourselves into one of the best universities in the world - which we are achieving through the talents and endeavour of every employee. Our high-achieving Advancement team recently closed its first global campaign, and is now building on this success to drive even greater philanthropic impact. Our high-achieving Advancement team recently closed its first global fundraising campaign, and is now building on this success to drive even greater philanthropic impact. The Advancement team of 25 ambitious professionals work with our global community of 153,000 alumni in 185 countries delivering alumni engagement activities and securing donations to support research and students at the University. The role We are seeking an outstanding assistant to provide high-quality, professional administrative and PA support to the Director of Advancement and the Advancement Leadership Team. This is a key role for an organised, proactive and personable individual who takes pride in delivering a seamless service, enabling senior leaders to operate effectively and efficiently within an ambitious Advancement function. The University operates a hybrid working approach and this role will be a minimum of three days per week office-based with flexibility to attend campus more frequently when required. Part-time hours will be considered for the right candidate. About you If you are highly efficient, dependable and trustworthy, with excellent administrative skills and a naturally warm and professional manner, we would welcome your application. You will join a friendly and forward-looking team at the University of Surrey, working in a collaborative environment and contributing to work that directly supports students, research and the University’s global ambitions.  How to apply To apply, please upload a CV and cover letter outlining why you would be a suitable candidate for the role. If you would like to discuss the role further, please contact Amintha Buckland, Associate Director, Philanthropy - a.buckland@surrey.ac.uk for an informal chat. Further details Job Description

The University of Vienna is a community of over 10,000 individuals, including approximately 7,500 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? We are currently seeking a/an University assistant predoctoral 60 Centre for Teacher Education Startdate: 01.03.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Reference no.: 5240 With 27 teaching subjects, one specialization and over 11,000 student teachers, the University of Vienna is the largest teacher training institution in Austria. At the Centre for Teacher Education (ZLB), we are working to bundle and further develop the various initiatives to improve the quality of teacher education. Together with the faculties and centres involved in teacher education and the universities of teacher education within the North-East Network, future teachers are prepared for the changing needs of a modern school and are enabled to contribute to shaping the learning and living environment of schools on the basis of scientific expertise.  Your personal sphere of influence: The advertised position is located at the Center for Teacher Education and is part of the doctoral program "Educational Innovation Needs Educational Research." As a University Assistant Praedoc, you will join the research team led by Prof. Susanne Schwab (Chair of School Pedagogy with a special focus on social, linguistic, and cultural diversity). The department deals with questions of school participation, inclusion and equal opportunities. We investigate how education systems, schools and teaching create conditions that can promote or limit the learning, well-being and development of children and young people. In doing so, we look at individual development processes as well as institutional and structural factors that shape educational paths. Our research is multi-perspective and interdisciplinary. It combines pedagogical, psychological and sociological approaches and examines education in all its complexity. Your future tasks: Development and expansion of an independent research profile Participation in the teams's research projects  Working on your dissertation and its completion Contribution to research, teaching, and institutional administration Student supervision Independent delivery of courses in accordance with collective agreement regulations This is part of your personality: Completed Master's or Diploma degree in Educational Sciences, Teacher Education, or a related social science discipline (e.g., Psychology) Initial experience in academic writing Very good knowledge of qualitative and/or quantitative research methods High level of written and verbal communication skills in German Very good proficiency in English, both spoken and written Proficiency in IT applications Ability to work effectively in a team Desirable qualifications: Knowledge of university processes and structures Didactic skills Experience in contributing to research projects Experience in pedagogical work with children and adolescents Additional language skills are desirable and advantageous (Arabic, Armenian, Turkish, Romanian, Bulgarian, etc.) What we offer: Work-life balance: Our employees enjoy flexible working hours and can partially work remotely. Contract duration: The employment duration is 3 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration. 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. Equal opportunities for all: We welcome every additional/new personality to the team!   It is that easy to apply: Motivation letter (Academic) CV Proof of project experience List of publications Proof of teaching experience (if available) Degree certificates Academic diplomas Via our job portal / Apply Now button If you have any questions, please contact: Susanne Schwab susanne.schwab@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: 02/16/2026  Prae Doc

Position Overview: Mohammed VI Polytechnic University (UM6P) invites applications for a highly qualified Postdoctoral Researcher to join our research initiative focusing on the integration of Artificial Intelligence (AI) in Chemical Process Systems Engineering (CPSE). The position addresses key challenges in process intensification, sustainability, and advanced process control, aiming to develop AI-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex chemical and biochemical processes. The research will contribute to next-generation smart manufacturing systems, aligned with Industry 4.0 paradigms, and target applications in sustainable energy production, green chemistry, circular economy, and carbon capture, utilization and storage (CCUS). Scientific Challenges Addressed in the Position: Non-linear and dynamic system modeling of chemical processes involving complex thermodynamics and transport phenomena. Optimization under uncertainty and robust decision-making for process design and operational strategies. Integration of first-principles (mechanistic) models with data-driven models (hybrid modeling) for improved accuracy and generalization. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data streams for reliable AI model training. Design of digital twins for process monitoring, fault diagnosis, and predictive maintenance in chemical plants. Key Responsibilities: Create and implement hybrid AI models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks and grey-box modeling) to enable predictive simulations of chemical and biochemical processes. Construct multi-objective optimization frameworks (Pareto optimization) to evaluate trade-offs among economic, energy efficiency, and environmental performance metrics. Utilize reinforcement learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical processes for virtual commissioning and optimization. Examine extensive heterogeneous data sets (including historical process data, sensor data, and laboratory findings) using advanced AI approaches such as unsupervised learning, transfer learning, and anomaly detection. Collaborate with process engineers and experimentalists to validate models, demonstrate them at pilot scales, and transfer technology to industry partners. Share research results through peer-reviewed publications, conference talks, and patent filings when relevant. Oversee graduate students and support capacity building in AI for CPSE at UM6P. Required Qualifications: Ph.D. in Chemical Engineering, Process Systems Engineering, Artificial Intelligence, Data Science, or a related discipline. Proven experience in process modeling (steady-state and dynamic) using simulation software such as Aspen Plus, gPROMS, or COMSOL Multiphysics. Solid understanding of process control strategies, including model predictive control (MPC), nonlinear control, and optimal control theory. Proficiency in programming languages (Python, MATLAB) and experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience in data-driven modeling, deep learning, and reinforcement learning algorithms applied to chemical processes. Track record of scientific publications in peer-reviewed journals in AI, chemical engineering, or process systems engineering. Excellent communication skills and ability to collaborate in multidisciplinary and international teams. Application Process: Candidates are invited to submit the following documents (compiled in a single PDF): A cover letter outlining their research vision, motivation, and relevant experiences. A comprehensive Curriculum Vitae (CV) including a list of publications and any patents. Contact details of two academic referees.