Umeå University 2022 PhD Student Position in Computational Science

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.

Umeå University 2022 PhD Student Position in Computational Science
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.