The food chain comprises agricultural production, manufacturing, distribution, retail and consumption. The agro-food sector is not only one of the largest manufacturing sector in Europe but also has a direct impact on the (environmental) health and vitality of the population. Food security and energy sustainability worldwide faces increased challenges arising from the globalisation of food trade, intensive production systems and changing consumer preferences. Predictive modelling and Quantitative (Microbial, Chemical) Risk Assessment plays a crucial part in food quality and safety around the globe, providing predictive tools which are used by the food industry, policy makers and managers to formulate and implement risk management policies and controls with the view to protecting human health.. In addition, Life Cycle Assessment is required in order to guarantee that the environmental vector is also included in the portfolio. The specific objectives of this strategic partnership (thematic area of Predictive Modelling and Quantitative Risk Assessment) are outlined hereunder: (i) to develop each participants capacity to design and generate informative experimental data, (ii) to build skills in developing or selecting modelling structures appropriate to describe quantitatively chemical, microbiological and physical phenomena and develop capabilities for quantifying accurately the sources of stochasticity, (iii) to make participants familiar with optimisation software and model simulation in research, that can be exploited for developing decision-making and quantitative risk assessment tools. (Iv) to open participants minds to the holistic approach encompasses by LCA in order to guarantee that environmental impacts are also considered and that transfer of burdens among stages of the value chains do not occur. (v) to expose participants to industrial environments and involve them with realistic problem based scenarios (vi) to increase employability of the participants during the coming years The target group of this strategic partnership are MSc or early stage PhD researchers working in the areas of public health, applied statistics, quantitative microbial/chemical risk assessment, food safety, process automation, food manufacturing. The programme will aim to promote an interactive participation, which will stimulate frank and open discussions between young and experienced postgraduate researchers. The main activities will include theoretical lectures that will be alternated with problem-based learning (PBL), student placements and dissemination activities. Theoretical lectures will cover all the fundamentals and basic principles of predictive modelling. Additionally, PBL pedagogical tools will be used in which students will work in groups to solve realistic multifaceted problems with the use of computer programming software. These problems will include the construction of experimental designs, model development, regression analysis, sensitivity analysis and safety risk scenarios. Placements will be accomplished for a number of students and external industrial, stakeholders and other participants will be participate in a dissemination event of a conference. By the end of the programme students will: (i) have attained a fundamental understanding of the substantial body of applied modelling, statistics and recent developments in the field of Predictive Modelling and Quantitative Risk Assessment of foods, (ii) have exercised personal responsibility and autonomous initiative in solving complex microbiological problems that are solved in a rigorous and professional approach, (iii) have engaged in critical dialogue and learned to criticise the broader implication of Applied Modelling approaches in Food Science through interactive teaching, (iv) have exploited available software packages and quantitative approaches for enriching current studies in the field in order to communicate results and innovations of research to peers, (v) are aware of the professional environment and (vi) have identified or be able to propose niche employability actions. The cooperation in the strategic partnership programme will result in a future knowledge transfer between participating institutions and facilitate the exchange of students for practical training in companies between the countries. Additionally, the multidisciplinary character of this strategic partnership will provide an unprecedented opportunity for researchers to communicate, collaborate and advance significantly beyond the current state-of-the-art supporting many pan European research projects as well as other international projects.