months, undermining food safety, cooperative efficiency, and smallholder income.

Processing challenges compound these losses. High microbial loads reduce pasteurization safety margins and destabilize fermented products such as yogurt and fresh cheese. Inconsistent starter performance, contamination during handling, and temperature fluctuations result in short shelf life (often less than 5-7 days), post-acidification defects, and variable texture. Yield variability limits cooperatives’ ability to scale higher-value products and weakens competitiveness. Women engaged in milk handling and rural youth often have limited access to training, infrastructure, and innovation, reinforcing inequalities and highlighting the need for a Leave No One Behind (LNOB) approach.

The SAFE-ID project supports a long-lasting shift in Indonesian smallholder dairy systems by improving hygiene, processing stability, and data-informed quality management. By reducing spoilage, strengthening milk safety, and promoting climate-resilient practices, it enables farmers and cooperatives to deliver higher-quality milk and dairy products despite tropical and infrastructure constraints. It directly contributes toSDG2, SDG12 and SDG9, and links to SDG3, SDG13 and SDG5. Through a Leave No One Behind approach, SAFE-ID promotes equitable access for women and rural youth to training, infrastructure, and innovation, strengthening inclusive participation and economic empowerment.

Impact occurs at multiple levels. Farmers gain practical tools to increase milk value and reduce losses. Cooperatives and processors benefit from more stable, standardized quality systems, improving competitiveness. Consumers access safer dairy products, while validated practices will inform provincial guidelines and extension programmes, enabling scale-up beyond pilot sites.

By embedding predictive modelling, antimicrobial surface strategies, and processing standardization within university laboratories, teaching farms, and cooperative networks, solutions remain locally grounded and institutionally anchored. Collaboration between universities, cooperatives, industry, and governmental bodies supports sustained innovation, safer food systems, stronger rural livelihoods, and more resilient dairy value chains aligned with Agenda 2030.

The SAFE-ID project integrates experimental research, predictive modelling, doctoral training, and structured stakeholder engagement to improve milk hygiene, safety, and processing stability in Indonesian smallholder dairy systems. Two complementary PhDs form the scientific/technological backbone, jointly addressing microbial contamination and physicochemical variability as interconnected drivers of quality loss.

1. PhD1 (KU Leuven - UNIMUS) "Development of Antimicrobial Milk-Contact Surfaces and Predictive Models to Improve Raw Milk Safety in Tropical Smallholder Dairy Systems" develops chitosan-based antimicrobial and anti-biofilm milk-contact surfaces, and models microbial (de-)contamination dynamics under tropical conditions. Work includes biofilm assays, microbial growth/inactivation kinetics, contamination pathway mapping, and hygiene protocol evaluation.
2. PhD2 (KU Leuven - UNDIP) "Improving Dairy Processing Stability through Experimental Dairy Science and Predictive Process Modelling in Tropical Climate" analyses raw milk physicochemical variability and its impact on pasteurization, fermentation, coagulation, and shelf-life. Controlled processing trials generate datasets to model processing performance enabling model based optimization.

PhD1 (KU Leuven - UNIMUS) "Antimicrobial Milk-Contact Surfaces for Raw Milk Safety" will:

• Develop biodegradable antimicrobial milk-contact coatings (e.g., chitosan-based systems),
• Investigate bacterial attachment and biofilm formation on dairy equipment,
• Evaluate antimicrobial efficacy against dairy spoilage microorganisms and pathogens,
• Characterize contamination pathways from farm to cooperative,
• Develop predictive microbial growth models under tropical temperature conditions,
• Design practical hygiene recommendations for smallholder dairy cooperative.

Expected outputs include:

• Novel antimicrobial milk-contact materials,
• Predictive microbial contamination models,
• Scientific publications in high-impact journals,
• Practical hygiene protocols for Indonesian dairy cooperatives,
• Decision-support tools for safer milk handling.

PhD2 (KU Leuven - UNDIP) "Improving Dairy Processing Stability" will:

• Characterize microbial and physicochemical variation in raw milk from Indonesian dairy cooperatives,
• Evaluate effects of milk composition on pasteurisation performance,
• Study fermentation kinetics for yoghurt production,
• Investigate coagulation behaviour for fresh cheese manufacture,
• Assess product shelf-life and quality stability,
• Develop predictive models linking raw milk quality with processing performance,
• Establish intake quality standards for dairy cooperatives.

Expected outputs include:

• Models predicting dairy processing performance,
• Improved milk intake criteria,
• Optimized processing protocols,
• Scientific publications,
• Practical decision-support tools for dairy cooperatives and processors.

We seek 2 highly motivated candidates with a background in food science & technology, (bio)chemical engineering, biotechnology, microbiology or a related field. The ideal candidates will possess:

• A master’s degree, with an excellent academic record,
• Interest in food processing, food microbiology, and food safety and quality,
• Ability to work both independently and as part of a team, collaborative spirit and innovative thinking,
• Experience with relevant lab-scale experimentation, data processing and scientific writing is a plus.

Language proficiency: Minimum B2 English (written/spoken). Non-native speakers must provide proof of competency. Join us in this exciting opportunity to create a joint innovation platform for improving milk hygiene, processing stability and data-driven quality management in Indonesian smallholder dairy systems. We offer 2 PhD positions:

• 4-year PhD programme (KU Leuven Arenberg Doctoral School), pending a positive evaluation by the doctoral committee at the end of the first year;
• Successful candidates will perform full-time research for 36 months in UNIMUS (PhD1) or UNDIP (PhD2), while completing 2 secondments of 6 months at KU Leuven/BioTeC+ in Gent, Belgium;
• Remuneration according to VLIRUOS SAFE-ID project budget;
• Supervision by leading experts at KU Leuven, UNIMUS and UNDIP;
• Dynamic research environments in Belgium and Indonesia;
• Opportunities to present at international conferences and publish in high ranking peer reviewed journals.

Next to the usual application documents as requested at the KU Leuven website (include your detailed CV, transcript of records, and any relevant publications so far), interested candidates are invited to submit:

• A cover letter outlining relevant experience and motivation for applying to either PhD1 or PhD2,
• A 3-page project proposal for the PhD position of their choice, outlining their interpretation of this call and detailing a project they would work on throughout the duration of their doctoral studies,
• Proof of language proficiency, and
• Contact details of 2 referees.

For more information please contact Prof. dr. ir. Jan Van Impe, mail: jan.vanimpe@kuleuven.be and Dr. ir. Monika Polanska, mail: monika.polanska@kuleuven.be.

months, undermining food safety, cooperative efficiency, and smallholder income.

Processing challenges compound these losses. High microbial loads reduce pasteurization safety margins and destabilize fermented products such as yogurt and fresh cheese. Inconsistent starter performance, contamination during handling, and temperature fluctuations result in short shelf life (often less than 5-7 days), post-acidification defects, and variable texture. Yield variability limits cooperatives’ ability to scale higher-value products and weakens competitiveness. Women engaged in milk handling and rural youth often have limited access to training, infrastructure, and innovation, reinforcing inequalities and highlighting the need for a Leave No One Behind (LNOB) approach.

The SAFE-ID project supports a long-lasting shift in Indonesian smallholder dairy systems by improving hygiene, processing stability, and data-informed quality management. By reducing spoilage, strengthening milk safety, and promoting climate-resilient practices, it enables farmers and cooperatives to deliver higher-quality milk and dairy products despite tropical and infrastructure constraints. It directly contributes toSDG2, SDG12 and SDG9, and links to SDG3, SDG13 and SDG5. Through a Leave No One Behind approach, SAFE-ID promotes equitable access for women and rural youth to training, infrastructure, and innovation, strengthening inclusive participation and economic empowerment.

Impact occurs at multiple levels. Farmers gain practical tools to increase milk value and reduce losses. Cooperatives and processors benefit from more stable, standardized quality systems, improving competitiveness. Consumers access safer dairy products, while validated practices will inform provincial guidelines and extension programmes, enabling scale-up beyond pilot sites.

By embedding predictive modelling, antimicrobial surface strategies, and processing standardization within university laboratories, teaching farms, and cooperative networks, solutions remain locally grounded and institutionally anchored. Collaboration between universities, cooperatives, industry, and governmental bodies supports sustained innovation, safer food systems, stronger rural livelihoods, and more resilient dairy value chains aligned with Agenda 2030.

The SAFE-ID project integrates experimental research, predictive modelling, doctoral training, and structured stakeholder engagement to improve milk hygiene, safety, and processing stability in Indonesian smallholder dairy systems. Two complementary PhDs form the scientific/technological backbone, jointly addressing microbial contamination and physicochemical variability as interconnected drivers of quality loss.

1. PhD1 (KU Leuven - UNIMUS) "Development of Antimicrobial Milk-Contact Surfaces and Predictive Models to Improve Raw Milk Safety in Tropical Smallholder Dairy Systems" develops chitosan-based antimicrobial and anti-biofilm milk-contact surfaces, and models microbial (de-)contamination dynamics under tropical conditions. Work includes biofilm assays, microbial growth/inactivation kinetics, contamination pathway mapping, and hygiene protocol evaluation.
2. PhD2 (KU Leuven - UNDIP) "Improving Dairy Processing Stability through Experimental Dairy Science and Predictive Process Modelling in Tropical Climate" analyses raw milk physicochemical variability and its impact on pasteurization, fermentation, coagulation, and shelf-life. Controlled processing trials generate datasets to model processing performance enabling model based optimization.

PhD1 (KU Leuven - UNIMUS) "Antimicrobial Milk-Contact Surfaces for Raw Milk Safety" will:

• Develop biodegradable antimicrobial milk-contact coatings (e.g., chitosan-based systems),
• Investigate bacterial attachment and biofilm formation on dairy equipment,
• Evaluate antimicrobial efficacy against dairy spoilage microorganisms and pathogens,
• Characterize contamination pathways from farm to cooperative,
• Develop predictive microbial growth models under tropical temperature conditions,
• Design practical hygiene recommendations for smallholder dairy cooperative.

Expected outputs include:

• Novel antimicrobial milk-contact materials,
• Predictive microbial contamination models,
• Scientific publications in high-impact journals,
• Practical hygiene protocols for Indonesian dairy cooperatives,
• Decision-support tools for safer milk handling.

PhD2 (KU Leuven - UNDIP) "Improving Dairy Processing Stability" will:

• Characterize microbial and physicochemical variation in raw milk from Indonesian dairy cooperatives,
• Evaluate effects of milk composition on pasteurisation performance,
• Study fermentation kinetics for yoghurt production,
• Investigate coagulation behaviour for fresh cheese manufacture,
• Assess product shelf-life and quality stability,
• Develop predictive models linking raw milk quality with processing performance,
• Establish intake quality standards for dairy cooperatives.

Expected outputs include:

• Models predicting dairy processing performance,
• Improved milk intake criteria,
• Optimized processing protocols,
• Scientific publications,
• Practical decision-support tools for dairy cooperatives and processors.

We seek 2 highly motivated candidates with a background in food science & technology, (bio)chemical engineering, biotechnology, microbiology or a related field. The ideal candidates will possess:

• A master’s degree, with an excellent academic record,
• Interest in food processing, food microbiology, and food safety and quality,
• Ability to work both independently and as part of a team, collaborative spirit and innovative thinking,
• Experience with relevant lab-scale experimentation, data processing and scientific writing is a plus.

Language proficiency: Minimum B2 English (written/spoken). Non-native speakers must provide proof of competency. Join us in this exciting opportunity to create a joint innovation platform for improving milk hygiene, processing stability and data-driven quality management in Indonesian smallholder dairy systems. We offer 2 PhD positions:

• 4-year PhD programme (KU Leuven Arenberg Doctoral School), pending a positive evaluation by the doctoral committee at the end of the first year;
• Successful candidates will perform full-time research for 36 months in UNIMUS (PhD1) or UNDIP (PhD2), while completing 2 secondments of 6 months at KU Leuven/BioTeC+ in Gent, Belgium;
• Remuneration according to VLIRUOS SAFE-ID project budget;
• Supervision by leading experts at KU Leuven, UNIMUS and UNDIP;
• Dynamic research environments in Belgium and Indonesia;
• Opportunities to present at international conferences and publish in high ranking peer reviewed journals.

Next to the usual application documents as requested at the KU Leuven website (include your detailed CV, transcript of records, and any relevant publications so far), interested candidates are invited to submit:

• A cover letter outlining relevant experience and motivation for applying to either PhD1 or PhD2,
• A 3-page project proposal for the PhD position of their choice, outlining their interpretation of this call and detailing a project they would work on throughout the duration of their doctoral studies,
• Proof of language proficiency, and
• Contact details of 2 referees.

For more information please contact Prof. dr. ir. Jan Van Impe, mail: jan.vanimpe@kuleuven.be and Dr. ir. Monika Polanska, mail: monika.polanska@kuleuven.be.