This will be the fifth successful MSCA project coordinated by the Institute of Structural Biology (STB), following on from ECO, BIGCHEM, AEGIS and AIDD, which have altogether contributed to the training of nearly 80 PhD fellows in environmental sciences, chemical biology, drug discovery, chemoinformatics and machine learning/AI. Many of the former PhD fellows have gone on to secure leading positions in industry and academia. The open call for PhD positions within AiChemist is still ongoing (https://aichemist.eu/openpositions).

“The main aim of the project is to develop advanced AI approaches with improved accuracy and explainability, with a specific focus on representation learning approaches for drug discovery. These machine-learning models will allow researchers to reliably and confidently predict the most decisive properties of drug candidates, such as toxicity, activity and optimal synthetic routes, based on their chemical structures. The ability to make such predictions would accelerate the drug discovery pipeline drastically, allowing pharmaceutical companies to decrease inefficient consumption of energy, feedstock and resources, and generate more promising leads” says Dr. Igor Tetko, who will coordinate the consortium of 25 partners, including four major pharmaceutical and life-science companies (Pfizer, Bayer, AstraZeneca, Sanofi and Syngenta) as well as public agencies such as European Chemical Agency (ECHA), US Food Drug Administration (FDA), the US National Institute of Environmental and Health Sciences (NIEHS) and several SMEs.

The fourteen fellows of the AiChemist program will closely cooperate with industry partners and will benefit from a highly structured and comprehensive curriculum delivered through regular online courses and schools. Three of the fellows will be supervised by Helmholtz-affiliated academics in close collaboration with Helmholtz AI (https://www.helmholtz.ai/).

The Marie Skłodowska-Curie Actions (MSCA) support researchers at all stages of their careers, regardless of their nationality. MSCAs also fund industrial doctorates, i.e. a combination of academic research work and work in large companies, SMEs, national regulatory bodies or research infrastructures, as well as other innovative training measures that improve employability and career development. In addition to generous research funding, scientists are given the opportunity to gain experience abroad and in the private sector, and to complement their training with skills or disciplines that are useful for their long-term career prospects and capacity for innovative cross-disciplinary research.

• artificial intelligence