The doctoral position is linked to the research project; “The European Partnership for Chemical Risk Assessment (PARC)": https://www.anses.fr/en/content/european-partnership-assessment-risks-chemicals-parc. The project involves several research fields including statistical modeling, machine learning, text mining, computational science, toxicology, epidemiology and environmental chemistry. Our part of the projects is primarily to develop computer-driven tools e.g. via machine learning, traditional statistical methods, and text mining, that allow for identifying new chemicals and predicting their effects. Big data will be generated in the projects where we are responsible for model development and interpretation.
You will work in a large network of European researchers in a project aimed at developing new methods for risk assessment of chemicals for environmental and human health protection.
Your mission will be to contribute in the development of an early warning system for detection of hazardous chemicals. This is critical for academia, stakeholders, policy makers but also industry to enable them to take action and avoid risk of exposure at a level of adverse effects of biota including humans. The mission includes developing text mining and data curation methods using artificial intelligence based methodologies and large scale inventory screenings. Data from various sources will be studied with the strive to identify indicators of hazards. Large amounts of data will be combined with biological markers for different physiological disorders with the purpose of understanding chemical triggers of hazardous effects. Machine learning based models will be developed in close collaboration with environmental chemists and (eco)toxicologists who provide underlying data and expertise. In summary, you will work with a variety of calculation-based methods with chemical and biological data. The project will be conducted in close collaboration with researchers from different disciplines and you are expected to play an active role in interdisciplinary cooperation.
The appointment aims at a PhD degree and the main task of the PhD student is to pursue their doctoral studies, which includes participation in research projects as well as postgraduate courses. In the assignments, teaching and other departmental work (up to a maximum of 20%) can be included. The employment is limited to four years full-time or up to five years when part-time teaching. The salary placement takes place according to the established salary level for doctoral employment.
To be admitted for studies at third-cycle level you are required to have completed a second-cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level or have an equivalent education from abroad, or equivalent qualifications.
To fulfil the specific entry requirements to be admitted for studies at third-cycle level in computational science and engineering, the applicant is required to have completed at least 90 credits in computational science and engineering courses, of which at least 30 credits shall have been acquired at second-cycle level. Computational science and engineering courses refers to courses with major quantitative, statistical or computing science elements, such as courses in computing science, mathematics and mathematical statistics. Applicants who in some other system either within Sweden or abroad have acquired largely equivalent skills are also eligible.
We are looking for a candidate who are interested machine learning, artificial intelligence, statistical modeling of large amounts of data with applications in the environmental chemistry and human health fields. Practical experience in computational chemistry and risk assessment of chemicals is meritorious but not a requirement. In addition, course credits in biology, ecology and chemistry is meritorious but not a requirement. Experience in analyzing large amounts of data using statistical or computing science methods is merit and experience of programming or software for advanced data evaluation (R, Python, MATLAB, Simca, KNIME, PBPK, PBTK, ADME, QSAR, etc.) is also desirable. As a person, you are careful and able to work independently. Good oral and written proficiency in English is also required.
A complete application should contain the following documents:
Applications must be submitted via our e-recruitment system no later than August 26, 2022.
For more information, please contact Professor Patrik Andersson, telephone +46-703039856, [email protected].
For more details, visit Umeå University website.