The PhD thesis is titled: Understanding chemical mixtures exposure and combination toxicity effects - A computational statistics approach'.
There are currently 5 planned projects/papers for this thesis:
- Exposure of adolescents to heavy metals, presistent organic pollutants, and rapidly excreted toxic subtsances in Sweden - the national survey Riksmaten Asolescents 2016-17
- Differences in chemical mixture exposure and associated determinants between different demographic groups of Swedish Adolescents
- Using machine-learning models to predict dioxin-like PCBs, PCDDs, and PCDFs in mothers milk from non-dioxin PCBs with comparison to standard methods.
- Combination toxicity of POPs in pregnancy. Influence on birth out-comes
- Combination toxicity of chemical substances/elements in children/adolescents. Vaccination antivodies as markers of immune function.
For the majority of the PhD projects, we are collaborating with the Swedish Food Agency for providing us with the RMU cohort and multiple laboratories (Stockholm University, Lund University, Finnish institute for health & welfare) doing the analysis of samples.
I am also currently collaborating with a team from Umea for project 3 where we are investigating different machine-learning models that can best predict dioxin-like PCBs, PCDDs and PCDFs in mother’s milk.
I have a masters degree in Infection Biology from Uppsala University and a bachelors degree in Microbiology from Nottingham Trent University. I have been working in a large range of projects prior to this PhD with focuses including campylobacter, salmonella, hantavirus, zika virus, epidemiology, insect ecology, agricultural plant ecology, tree husbandry/pests and prion diseases.
I have self-taught myself programming using R and Python which I use on a near-daily basis for my PhD work.
My PhD supervisor is Anders Glynn.
Projects 1 and 2 are near full manuscript completion and will be published here when accepted.