Eniola's strongest angle is a dual-track biosecurity + AI safety pitch centred on IMPRINT and TOPOLOGIX as safety infrastructure, not just research outputs. For biosecurity: frame IMPRINT (addiction-liability screener) explicitly as a pre-weaponisation detection tool for synthetic CNS drug candidates — the same computational pipeline that predicts reward-circuit encoding probability for therapeutic design also flags whether a novel opioid analogue would produce extreme addiction liability before it escapes into illicit supply chains or is deliberately weaponised, a direct GCBR concern given AI-assisted molecular design. For AI safety: TOPOLOGIX's TDA-driven drug-protein interaction framework provides mechanistic ground truth that current RL-based drug-discovery AI systems lack; without it, generative AI models optimising for drug-target affinity will inadvertently optimise for reward-circuit engagement, producing dangerous candidates at scale. The funded activity to propose is the 12-month pre-MSc independent research and transition period (July 2026–October 2026 plus MSc Year 1 support at MUG Graz from October 2026) — framed as 'converting my CCT computational pipeline into open-source biosecurity screening infrastructure and completing the degree that gives me institutional standing to publish and deploy it.' The endorsements from Berridge, Gershman, Daw, and Mattar — all leading reward-neuroscience figures — should be cited as external validation that the mechanistic grounding is credible, not speculative.