PhD Position in Cheminformatics and Machine Learning

Syddansk Universitet; Odense; On-site; DKK 379,000 - 454,000; Full time

Job summary

University of Southern Denmark invites applications for a PhD position in Cheminformatics and Machine Learning within the SDU Life Cycle Engineering department. The project contributes to PFAROS, focusing on sustainable healthcare and safer chemical innovations through data-driven approaches and cross-disciplinary collaboration.

The successful candidate will work on collecting data, building predictive models, and integrating experimental results with computational workflows, under the PFAROS

Qualifications

• Master’s degree in chemistry, environmental science, chemical engineering, computer science, data science, 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 data for chemicals in commerce.
• Evaluate applicability domains and coverage of existing ML models for chemical properties.
• Develop, train, validate, and benchmark new models for chemical property prediction.
• Contribute to integration of experimental data, computational methods, and ML workflows.
• Collaborate with international project partners and contribute to publications and proposals.

Skills

Python

Machine learning

Data science

English comms

Education

MSc degree

Tools

Cheminformatics tools

Job description

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.

The main tasks include:

• 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.

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 Wang
DIAS Professor
Department of Green Technology
SDU Life Cycle Engineering
University of Southern Denmark
Email: [e-mail]

Assessment of candidates is based on the application material, and the application must include:

• Motivated application.
• Master’s and Bachelor’s degree certificates or equivalent, including transcripts of grades(original and an official English translation).
• Completed TEK PhD application form for 5+3 applicants. Find the form at the Faculty website .
• Completed TEK PhD form for calculation grade point average. Find the form at the Faculty website .
• An official document describing the grading scheme of the awarding universities (if not Danish).
• Only for applicants from programmes that evaluate thesis/examination project by approved/not approved: An official written assessment of the thesis or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme.
• List of publications and maximum 2 examples of relevant publications (in case you have any publications).
• References may be included, you're welcome to use the form for reference letter at the Faculty website .
• A statement/documentation of other qualifications relevant to the position may also be included.
• All documents must be in English and PDF format. CPR number (civil registration number) must be crossed out. All PDF-files must be unlocked, allow binding and may not be password protected.
• SUBMISSION GUIDE: Motivated application must be uploaded under ‘Cover letter’ (max. 5 MB), Curriculum Vitae must be uploaded under ‘Resume’ (max 5 MB). All other documents must be uploaded under ‘Miscellaneous documents’ (max 10 files with a maximum 50 MB per file).
• The application deadline isNovember 12, 2026, at 11:59 PM/23:59 (CET/CEST)

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.

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).