PhD Position in Cheminformatics and Machine Learning

Cph Ai Hub; Odense; Hybrid; DKK 379,000 - 454,000; Full time

Job summary

University of Southern Denmark’s SDU Life Cycle Engineering invites applications for a PhD fellowship in cheminformatics and machine learning. The role integrates chemistry, AI, and data science to advance chemical risk assessment for PFAS-free healthcare within the PFAROS consortium.

The position is based in Odense and affiliated with the Department of Green Technology. Responsibilities include data curation, model development, and collaboration across international partners, with a strong

Qualifications

• MSc degree (or equivalent) in chemistry, environmental science, chemical engineering, computer science, data science, bioinformatics, or related field.
• Strong interest in machine learning, cheminformatics, data science, and chemical risk assessment.
• Experience with programming in Python and scientific computing.
• Familiarity with machine learning methods, data management, and statistical analysis.
• Experience with chemical databases, molecular descriptors, QSAR models, or cheminformatics tools is an advantage.
• Excellent written and oral communication skills in English.

Responsibilities

• Collect, curate, and validate high-quality physicochemical, environmental, and hazard data for chemicals in commerce.
• Evaluate and document applicability domains and coverage of existing ML models for predicting chemical properties.
• Develop, train, validate, and benchmark new models for chemical property prediction, including ML and generative AI-based approaches.
• Contribute to integration of experimental data, computational methods, and ML workflows.
• Participate in collaborative research within the PFAROS consortium and interact with international partners.
• Contribute to publications, conference presentations, reports, and new research proposals.

Skills

Python programming

Machine learning

Data management

Communication skills

Independence & teamwork

Education

MSc in related field

Tools

Cheminformatics tools

Job description

SDU Life Cycle Engineering at the Department of Green Technology, University of Southern Denmark, invites applications for a PhD position in cheminformatics and machine learning.

The position will contribute to PFAROS, a flagship European research project dedicated to driving sustainable innovation and supporting the transition toward PFAS-free healthcare in Europe. Working at the intersection of chemistry, environmental science, artificial intelligence, and data science, the successful candidate will help advance next-generation approaches for chemical assessment by integrating diverse data streams, developing cutting-edge predictive models, and generating knowledge that supports safer and more sustainable chemical and material innovation. Through collaboration with leading international researchers and stakeholders, the position offers a unique opportunity to contribute to high-impact science addressing some of society’s most pressing environmental and health challenges.

The position will contribute to ongoing research projects and activities at SDU Life Cycle Engineering.

Main tasks

• Collect, curate, and validate high-quality physicochemical, environmental, and hazard property data for chemicals in commerce.
• Evaluate and document the applicability domains and coverage of existing machine learning models used for predicting chemical properties.
• Develop, train, validate, and benchmark new models for chemical property prediction, including machine learning and generative AI-based approaches.
• Contribute to the integration of experimental data, computational methods, and machine learning workflows.
• Participate in collaborative research activities within the PFAROS consortium and interact with international project partners.
• Contribute to scientific publications, conference presentations, reports, and the development of new research proposals.

Qualifications

• MSc degree (or equivalent) in chemistry, environmental science, chemical engineering, computer science, data science, bioinformatics, or a related field.
• Strong interest in machine learning, cheminformatics, data science, and chemical risk assessment.
• Experience with programming in Python and scientific computing.
• Familiarity with machine learning methods, data management, and statistical analysis.
• Experience with chemical databases, molecular descriptors, QSAR models, or cheminformatics tools is an advantage.
• Excellent written and oral communication skills in English.
• Ability to work independently as well as collaboratively in an international research environment.

SDU Life Cycle Engineering

The successful candidate will be affiliated with SDU Life Cycle Engineering at the Department of Green Technology. The research environment conducts interdisciplinary research on the global and systemic interactions between materials, technologies, energy, the environment and society.

The Department of Green Technology is located in Odense, the main campus of the University of Southern Denmark. Odense offers an international research environment and an open Scandinavian working culture.

Further Information

Further information about the scientific content of the position is available from:

Zhanyun WangDIAS ProfessorDepartment of Green TechnologySDU Life Cycle EngineeringUniversity of Southern DenmarkEmail:

If you experience technical problems, please contact our email support.

Assessment and selection process

Applications will be assessed by an expert. Shortlisting may be applied, and only shortlisted candidates will receive a written assessment. Read about shortlisting at SDU. Interviews and tests may be part of the overall evaluation.

Read about the Assessment and selection process.

Enrollment and employment terms

Appointment as a PhD fellow is a 3-year salaried position, and the monthly gross salary incl. pension is 37.313 DKK. If you have relevant postgraduate experience, you may be placed on a higher salary step.

The preferred start date is in January 2026.

Applicants must hold a master’s degree (equivalent to a Danish master's degree) at the time of enrollment and employment. Employment is contingent on enrollment approved by the PhD School. Enrollment will be in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order). Employment will be in accordance with the collective agreement between the Ministry of Finance and the Danish Confederation of Professional Associations for academics in the state including the associated circular on the job structure for academic staff at Danish universities and the provisions for PhD fellows as described therein as well as the Protocol on PhD fellows signed by the Danish Ministry of Finance and the Danish Confederation of Professional Associations (AC).

Salary is determined in accordance with the applicable collective agreement and based on objective and gender-neutral criteria, including the content of the position, responsibilities, and qualification requirements. As an applicant, you are entitled to information about the starting salary and salary range for the position. This information will be provided during the recruitment process. SDU does not collect information on applicants’ previous salary. Further information on salary and taxation.

Persons employed in the position may, based on a specific individual managerial assessment, be exempted from time registration, also known as a “self-organizer”.

The University of Southern Denmark wishes its staff to reflect the surrounding community and therefore encourages everyone, regardless of personal background, to apply for the position. SDU conducts research in critical technologies, which, due to the risk of unwanted knowledge transfer, is subject to a number of security measures. Therefore, based on information from open sources, background checks may be conducted on candidates for the position(s).

Further information for international applicants about entering and working in Denmark. You may also visit WorkinDenmark for additional information.

Further information about The Faculty of Engineering.