Powering data-driven sustainability assessment tasks in Agri-food systems with IoT-data Data-lakes and large language models
fuldtid
Powering data-driven sustainability assessment tasks in Agri-food systems with IoT-data Data-lakes and large language models
Applicants are invited for a double degree PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 September 2026 or later. You can submit your application via the link under 'how to apply'.
The position is part of the MSCA project GreenFieldData - IoRT Data management and analysis for Sustainable Agriculture, ID: 101226371, Call: HORIZON-MSCA-2024-DN-01. Link to the portal of the project https://www.eu4greenfielddata.eu/
Note that this is a double degree PhD project. Therefore, the employment will be at Aarhus University, but the place of work will be split equally between Aarhus University, Denmark, and Université Libre Bruxelles, Belgium.
Title
Powering data-driven sustainability assessment tasks in Agri-food systems with IoT-data Data-lakes and large language models
Research area and project description
Digitization and the interconnection of agriculture processes are key to delivering national and international sustainability goals such as climate-smart and environmentally sustainable Agri-food systems sectors. Digitalization is the necessary precondition for scalable and sustainable Agri-food systems. In this context, Internet of Things (IoT) services, not only the connection and integration of devices that monitor the physical world (e.g., temperature, pollution, energy consumption, emissions) but also analytics of information including data represented as a collection of time sequences of events (i.e., time series data) that those devices create to derive insights and take appropriate actions. However, this relies on creating an environment where data is curated, standardized, integrated, and organized while Ag-tech stakeholders can create new value from this data effectively and efficiently.
More specifically, data-driven assessment tasks and processes (e.g., LCA-Life-Cycle Assessment-based processes) in accounting for effects, trade-offs, and synergies between different mitigation activities in the efforts to reduce climate impact and increase sustainability in Agri-food systems may leverage analytics over data lakes for extracting knowledge and deriving insights from the vastly growing amounts of local, external and open data nonetheless. In contrast, advances in data analytics enable automation and scalability opportunities, and new productivity and usability challenges emerge, especially in large-scale data lakes involving structured, semi-structured, and unstructured time series data. Specifically, agricultural data is diverse in terms of format and content, fragmentation, metadata description, standards, and semantics, which means that the interoperability problem exists both at the technical and semantic levels.
This PhD aim to advance novel techniques to scale and simplify data-driven impact assessment processes making them intuitive, powerful, and accessible to end users, by leveraging large language models (LLMs). LLMs are pre-trained on broad data and can be adapted to diverse tasks, from question answering, and summarization, to data wrangling. More specifically, the aim is to provide users with a single-entry point where they define and structure express assessment tasks in a natural way (e.g., text) and interact with data lakes to perform such tasks.
Specific objectives include:
1. Develop methods for assessing climate impacts (e.g. GHG emissions) in the robotized cereals production system by means of Life Cycle Assessment (LCA) and innovative generic methods
2. Make them intuitive, powerful, and accessible to end users, by leveraging gender inclusive large language models (LLMs) (Task 3.2).
3. LLMs are pre-trained on broad data and adapted to diverse tasks, from question answering, summarization, to data wrangling. The users are provided with a single-entry point for definition and structuring assessment tasks in a natural way (e.g. text) and interact with data lakes to perform such tasks.
Project description
For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application.
Salary, holiday payment, pension contributions and the like include all employer and employee's taxes and contributions. Thus, figures are before taxes are paid, and taxes may differ depending on individual circumstances. Salary and terms of employment are in accordance with applicable collective agreement, and salary is depending on seniority. Salary includes a non-pensionable PhD supplement. The allowances mentioned in the EU work programme (living allowance, mobility allowance and, if applicable, family allowance) will be part of the salary. Allowance rates can be found in the relevant EU Work Programme (under MSCA doctoral network - Applicable unit contributions), and country correction coefficient can be found in the same document.
Qualifications and specific competences
Applicants to the PhD position must have a master’s degree in computer science (120 ECTS). General Criteria:
Required skills:
Place of employment and place of work
Note that this is a double degree PhD project.
The place of employment is at Aarhus University, but the place of work will be split equally between the two universities involved in the double degree project.
The place of work at Aarhus University is Bygn. 8210, Blichers Allé 208830 Tjele, AU Viborg, Denmark. The place of work at Université Libre Bruxelles, Belgium is Dept. of Computer and Decision Eng., Data Science and Engineering lab, Bruxelles, Belgium.
EU eligibility requirements in Marie Curie Doctoral Networks
Contacts
Applicants seeking further information regarding the PhD position are invited to contact:
For information about application requirements and mandatory attachments, please see our application guide. If answers cannot be found there, please contact:
How to apply
Please follow this link to submit your application.
Application deadline is 15 April 2026 at 23:59 CEST
Preferred starting date is 01 September 2026.
Please note:
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.
The position is part of the MSCA project GreenFieldData - IoRT Data management and analysis for Sustainable Agriculture, ID: 101226371, Call: HORIZON-MSCA-2024-DN-01. Link to the portal of the project https://www.eu4greenfielddata.eu/
Note that this is a double degree PhD project. Therefore, the employment will be at Aarhus University, but the place of work will be split equally between Aarhus University, Denmark, and Université Libre Bruxelles, Belgium.
Title
Powering data-driven sustainability assessment tasks in Agri-food systems with IoT-data Data-lakes and large language models
Research area and project description
Digitization and the interconnection of agriculture processes are key to delivering national and international sustainability goals such as climate-smart and environmentally sustainable Agri-food systems sectors. Digitalization is the necessary precondition for scalable and sustainable Agri-food systems. In this context, Internet of Things (IoT) services, not only the connection and integration of devices that monitor the physical world (e.g., temperature, pollution, energy consumption, emissions) but also analytics of information including data represented as a collection of time sequences of events (i.e., time series data) that those devices create to derive insights and take appropriate actions. However, this relies on creating an environment where data is curated, standardized, integrated, and organized while Ag-tech stakeholders can create new value from this data effectively and efficiently.
More specifically, data-driven assessment tasks and processes (e.g., LCA-Life-Cycle Assessment-based processes) in accounting for effects, trade-offs, and synergies between different mitigation activities in the efforts to reduce climate impact and increase sustainability in Agri-food systems may leverage analytics over data lakes for extracting knowledge and deriving insights from the vastly growing amounts of local, external and open data nonetheless. In contrast, advances in data analytics enable automation and scalability opportunities, and new productivity and usability challenges emerge, especially in large-scale data lakes involving structured, semi-structured, and unstructured time series data. Specifically, agricultural data is diverse in terms of format and content, fragmentation, metadata description, standards, and semantics, which means that the interoperability problem exists both at the technical and semantic levels.
This PhD aim to advance novel techniques to scale and simplify data-driven impact assessment processes making them intuitive, powerful, and accessible to end users, by leveraging large language models (LLMs). LLMs are pre-trained on broad data and can be adapted to diverse tasks, from question answering, and summarization, to data wrangling. More specifically, the aim is to provide users with a single-entry point where they define and structure express assessment tasks in a natural way (e.g., text) and interact with data lakes to perform such tasks.
Specific objectives include:
1. Develop methods for assessing climate impacts (e.g. GHG emissions) in the robotized cereals production system by means of Life Cycle Assessment (LCA) and innovative generic methods
2. Make them intuitive, powerful, and accessible to end users, by leveraging gender inclusive large language models (LLMs) (Task 3.2).
3. LLMs are pre-trained on broad data and adapted to diverse tasks, from question answering, summarization, to data wrangling. The users are provided with a single-entry point for definition and structuring assessment tasks in a natural way (e.g. text) and interact with data lakes to perform such tasks.
Project description
For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application.
Salary, holiday payment, pension contributions and the like include all employer and employee's taxes and contributions. Thus, figures are before taxes are paid, and taxes may differ depending on individual circumstances. Salary and terms of employment are in accordance with applicable collective agreement, and salary is depending on seniority. Salary includes a non-pensionable PhD supplement. The allowances mentioned in the EU work programme (living allowance, mobility allowance and, if applicable, family allowance) will be part of the salary. Allowance rates can be found in the relevant EU Work Programme (under MSCA doctoral network - Applicable unit contributions), and country correction coefficient can be found in the same document.
Qualifications and specific competences
Applicants to the PhD position must have a master’s degree in computer science (120 ECTS). General Criteria:
- MSCA Mobility Rule: researchers must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 36 months immediately before their date of recruitment
- All researchers recruited in a DN must be doctoral candidates (i.e. not already in possession of a doctoral degree at the date of the recruitment)
- An applicant must have received the equivalent of 300 ECTS with a major in computer science, from which at least 60 ECTS corresponds to a master’s degree. The master’s degree must be granted by a university recognized by the International Association of Universities.
- Scientific excellence to fit the PhD project
- Fluent (oral and written) English skills as the project operates in English language
- Knowledge of the language of the host country may be considered a merit
- Team-mindedness
Required skills:
- Advanced databases and programming skills
- Advanced operations research skills (optimization, graph theory, logistic models)
- Interdisciplinary work
Place of employment and place of work
Note that this is a double degree PhD project.
The place of employment is at Aarhus University, but the place of work will be split equally between the two universities involved in the double degree project.
The place of work at Aarhus University is Bygn. 8210, Blichers Allé 208830 Tjele, AU Viborg, Denmark. The place of work at Université Libre Bruxelles, Belgium is Dept. of Computer and Decision Eng., Data Science and Engineering lab, Bruxelles, Belgium.
EU eligibility requirements in Marie Curie Doctoral Networks
- Supported researchers must be doctoral candidates, i.e. not already in possession of a doctoral degree at the date of the recruitment. Researchers who have successfully defended their doctoral thesis, but who have not yet formally been awarded the doctoral degree will not be considered eligible.
- Researchers supported must be enrolled in a doctoral programme leading to the award of a doctoral degree in at least one EU Member State or Horizon Europe Associated Country, and for Joint Doctorates in at least two.
- Recruited researchers can be of any nationality and must comply with the following mobility rule: they must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 36 months immediately before their recruitment date.
- Compulsory national service, short stays such as holidays and time spent by the researcher as part of a procedure for obtaining refugee status under the Geneva Convention75 are not considered.
- Secondments are eligible for up to one third of the actual months spent implementing the research training activities under the action.
- In case of industrial doctorates, doctoral candidates must spend at least 50% of their fellowship duration in the non-academic sector.’
Contacts
Applicants seeking further information regarding the PhD position are invited to contact:
- Claus Aage Grøn Sørensen, claus.soerensen@ece.au.dk (main supervisor)
- Dimitris Sacharidis, dimitris.sacharidis@ulb.be (co-supervisor)
For information about application requirements and mandatory attachments, please see our application guide. If answers cannot be found there, please contact:
How to apply
Please follow this link to submit your application.
Application deadline is 15 April 2026 at 23:59 CEST
Preferred starting date is 01 September 2026.
Please note:
- Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be considered.
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.