Natural Traces

MARIE SKŁODOWSKA-CURIE ACTIONS - Call: HORIZON-MSCA-2022-DN-01-01 

Grant agreement ID: 101120165

https://cordis.europa.eu/project/id/101120165

A doctoral network funded by Marie Skłodowska-Curie Actions (MSCA) which is a part of Horizon Europe, the MSCA are the European Union’s flagship funding programme for doctoral education and postdoctoral training of researchers.



Literally any crime scene contains animal, plant, soil, microbial or environmental traces. Examples include pet hairs or saliva, pollen and algae, soil and soil organisms like bacteria or nematodes, fungal spores, insects, and invironmental traces in the form of environmental DNA of any origin. Such biological traces can be found mainly on living people (suspects, victims), on objects like cars or weapons, and on bodies not just on the surface but also in their surroundings like single or mass graves, or an aquatic environment.

In the EU, there is a lack of training opportunities in applied topics of forensic science at postgraduate level, such as the qualitative and quantitative analysis of specifically such non-human biological traces. While many EU countries have forensic laboratories that also such traces, a much broader, integrated knowledge base is needed, built on close cooperation between basic research in academia and analysis and application in casework by forensic specialists. NATURAL TRACES aims to optimise the procedures for taking and analysing non-human traces in order to meet the ever-increasing demands for identifying suspects and victims and to link traces to different places, times or courses of action. The results based on this need a statistical robustness that will also hold up in the

courtroom under cross-examination.

The proposal aims for 11 PhD students with a background in life sciences. They will build their knowledge and experience in practical forensics in training schools provided by academic, non-academic partners, and police academies or laboratories. The training embeds biological evidence in a Bayesian framework, making it universally comparable with all other forms of evidence, by applying novel probabilistic approaches to extract forensic useful information from metadata. It is truly cross-sectoral, with secondments at end-users of the training (e.g. police forces) and joint supervision by PIs from different countries.