Marie Curie PhD Position; Doctoral ) in AI-driven Drug Discovery

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Date:
Wed Feb 11 16:49:27 2026

Marie Curie PhD Position (Doctoral Candidate) in AI-driven Drug Discovery Biomedical Research Foundation, Academy of Athens (BRFAA) OFFER DESCRIPTION

1 doctoral candidate position is available within the EU-funded Marie Skodowska Curie Doctoral Network in the LowDataML Doctoral Network (Low Data Machine Learning for Sustainable Chemical Sciences) under Grant Agreement No. , at the BIOMEDICAL RESEARCH FOUNDATION ACADEMY OF ATHENS (BRFAA), Greece

The LowDataML project aims to train 10 doctoral researchers to pioneer low-data machine learning (ML) approaches for the chemical and life sciences, promoting sustainable and resource-efficient innovation in drug discovery, reaction optimization, and molecular design. The network brings together academic and industrial partners from across Europe and Canada to advance AI-driven, eco-friendly chemical research with real-world impact. Project website:

We provide a structured 36-month PhD training programme within the Marie Skodowska-Curie Doctoral Network LowDataML (Low Data Machine Learning for Sustainable Chemical Sciences). The programme offers cutting-edge research and training at the intersection of machine learning, computational chemistry, biophysics, bioinformatics, and drug discovery. The earliest starting date is 1 December 2025, and the latest is 1 March 2026.

We are looking for a highly motivated and talented early-stage researcher eager to pursue doctoral studies in the fields of AI-driven molecular design, computational drug discovery, and physical chemistry of biological systems.

Applicants should hold a Masters degree (or equivalent) in Computational Biology, Chemistry, Physics, Computer Science, or related disciplines. Previous experience in machine learning, molecular dynamics, or computational chemistry is desirable. Excellent command of spoken and written English, communication skills, and the ability to work in a collaborative international environment are essential.

We offer a stimulating and interdisciplinary research environment with access to state-of-the-art computational and experimental facilities and a strong track record of collaboration between academia and industry. In addition to individual training-through-research, fellows will participate in network-wide workshops, summer schools, transferable skills courses, and international secondments at partner institutions.

The following eligibility rules apply for participation in a Marie Skodowska Curie Innovative Doctoral Network:
Applicants must be in the first 4 years after obtaining their Masters degree and/or Bachelors degree and must not have resided or carried out their main activity (work, studies, etc.) in the host country for more than 12 months in the 3 years immediately before the recruitment date. In addition, local regulations of the host countries may apply. The salary is based on standard living, mobility and family allowances which are adapted to the respective country of recruitment.

ESR 1:
Design of novel c-Myc inhibitors Host Organisation: BRFAA Scientist-in-Charge:
Dr. Zoe Cournia Contact email:
Applicants should apply by email to zcournia ~~ bio academy.gr indicating Reference: .

The PhD project aims to design novel c-Myc inhibitors using advanced machine learning (ML) methods. c-Myc deregulation is associated with poor prognosis in cancer and has long been considered an "undruggable" target. The successful candidate will:

• Train N-shot neural networks (e.g., Siamese networks) on fingerprints of known c-Myc Max inhibitors to identify new putative inhibitors.
• Explore large chemical databases (ZINC, ChEMBL) and apply virtual screening to reduce the search space for drug discovery.
• Evaluate candidate molecules using molecular dynamics simulations and empirical scoring functions.
• Run biophysical (CD, microscale thermophoresis) and cell-based assays for validation.

• Development of a robust N-shot neural network for novel inhibitor discovery.
• Identification of new small molecules disrupting c-Myc Max dimerization.

The PhD candidate will have research stays (secondments) at:

• UCAM (University of Cambridge) 3 months
• chemical biology FUB (Free University of Berlin) 3 months
• physics-based modelling ARQ…