MOTIVATION LETTER The Conjunctive Consolidation Threshold model, or CCT, is a tripartite pharmacological framework for preventing reward-memory encoding in addiction. It couples three axes, dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast, into a single system of ordinary differential equations solved with RK45 and calibrated through Bayesian MCMC using PyMC's DEMetropolisZ sampler with 14 free parameters. The priors were elicited from a systematic screen of 1,847 records in the literature. All five pre-registered hypotheses, H1 through H5, were confirmed, and the posterior shows super-additivity of 13 to 22 percentage points across model versions. This is the research line I propose to develop as an EMBO Postdoctoral Fellow. EMBO's selection criteria emphasize scientific excellence evidenced by publications and preprints, international mobility, and the quality and feasibility of the research proposal. My record includes three sole-authored preprints on the CCT model, each currently under review at a peer-reviewed journal (IART, PNPBP, and NBR), plus a co-authored paper under review at Alcohol (Elsevier). The model has been endorsed in correspondence with Kent Berridge at Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU. Gershman has provided an arXiv endorsement. These are named researchers whose work defines the current state of computational reinforcement learning and affective neuroscience. The CCT model fits EMBO's life sciences mandate because it is fundamentally a quantitative biology project. It makes a falsifiable claim about how three distinct molecular and circuit-level mechanisms interact to consolidate reward memories, and it generates dose-response predictions that can be tested in animal models. The Bayesian calibration framework means every parameter carries an uncertainty estimate, and the pre-registration of all five hypotheses means the confirmatory results are not post-hoc. This is the standard of evidence EMBO expects. I am currently enrolled in the M.Sc. Digital Health programme at the Hasso Plattner Institute / University of Potsdam, Germany, and I hold a B.Pharm from the University of Ibadan with a German equivalent grade of 1.9. I am a PCN-licensed pharmacist. The EMBO fellowship requires a doctoral degree or equivalent, and I am actively seeking a PhD position in computational neuroscience to complete this requirement. The fellowship's rolling deadline and its support for international mobility align with my trajectory: I am a Nigerian researcher moving into the European system, and I intend to conduct the proposed work in a host laboratory in Germany or another EMBO member state. The CCT model is the most mature and most externally validated line of my research, and it is the one with the clearest path to experimental testing. I am applying to EMBO because the fellowship's emphasis on rigorous, pre-registered, quantitative life sciences research matches exactly how I work. RESEARCH STATEMENT The CCT model addresses a specific gap in addiction neuroscience: no existing framework explains why some pharmacological interventions block reward-memory reconsolidation while others only attenuate it. The model posits a conjunctive threshold, a point at which dopaminergic reward prediction error, NMDAR-dependent plasticity, and affective contrast must all cross a joint boundary for memory encoding to proceed. Below that threshold, the memory is not consolidated. The three axes are coupled, and the coupling is what produces the super-additive effects observed in the posterior. The mathematical structure is a system of coupled ODEs solved with RK45. The parameters were estimated with PyMC using DEMetropolisZ, a Markov chain Monte Carlo sampler suited to high-dimensional posteriors. The 14 free parameters were given priors elicited from a structured screen of 1,847 records from the addiction and memory literature. The model was pre-registered with five hypotheses, H1 through H5, and all five were confirmed. The posterior shows that the combined effect of the three axes exceeds the sum of their individual effects by 13 to 22 percentage points, depending on model version. This super-additivity is the model's central quantitative claim. The proposal for the EMBO fellowship period has three aims. First, to extend the CCT model from a fixed-parameter ODE system to a stochastic differential equation framework that can represent trial-to-trial variability in reward prediction error. This will make the model's predictions directly comparable to single-neuron and behavioral time-series data from rodent self-administration paradigms. Second, to fit the model to existing published datasets from reconsolidation blockade experiments, using the same Bayesian calibration pipeline already validated on the CCT model. This will test whether the model's predictions hold across experimental paradigms, not just in silico. Third, to generate a set of falsifiable dose-response predictions for specific pharmacological agents, prioritized by their receptor profiles, that a collaborating experimental laboratory can test. The methods are already in place. I have built and validated the calibration pipeline. I have run the sensitivity analyses. I have the endorsements of Berridge, Gershman, Daw, and Mattar, all of whom work at the intersection of computational and experimental neuroscience. What the EMBO fellowship provides is the protected time and the host laboratory environment to move from a calibrated in silico model to a model that makes contact with experimental data. The CCT model is the right line of research for EMBO because it is a life sciences project with a quantitative core. It is a mechanistic hypothesis about how the brain consolidates reward memories, expressed in equations and calibrated against evidence. EMBO's mandate is to support exactly this kind of research. SHORT-ANSWER ESSAY: INTERNATIONAL MOBILITY I am a Nigerian citizen currently enrolled in the M.Sc. Digital Health programme at the Hasso Plattner Institute / University of Potsdam in Germany. My undergraduate degree is from the University of Ibadan, Nigeria. The EMBO Postdoctoral Fellowship requires mobility to a new host country, and my trajectory satisfies this requirement in two ways. First, I have already moved from Nigeria to Germany for my graduate studies, demonstrating the capacity to relocate and establish a productive research life in a new scientific culture. Second, the proposed host laboratory for the fellowship period will be in Germany or another EMBO member state, which constitutes a new research environment distinct from my current institution. The fellowship's support for relocation and family allowances is material to this move. I am applying from outside the European Research Area's core, and my research network, including endorsements from Berridge, Gershman, Daw, and Mattar, spans the US and Europe, which means I can integrate into a new host lab while maintaining productive collaborations across institutions. SHORT-ANSWER ESSAY: SCIENTIFIC EXCELLENCE My scientific record is built on pre-registered, falsifiable, quantitatively rigorous work. The CCT model has three sole-authored preprints, each under review at a peer-reviewed journal, and a co-authored paper under review at Alcohol (Elsevier). All five pre-registered hypotheses were confirmed. The model's Bayesian calibration used 14 free parameters with literature-elicited priors from a 1,847-record screen, and the posterior super-additivity of 13 to 22 percentage points is a specific, checkable result. I have also conducted two replication studies in topological data analysis applied to drug safety and resistance. The first, on hERG cardiotoxicity, found that bipartite persistent homology does not beat a plain descriptor baseline (AUROC 0.8426 vs 0.8782), settling a comparison the literature had never run. The second, on drug-resistance prediction, found that interface topology carries almost no signal (AUROC 0.425 and 0.485 on the Platinum benchmark), which motivated my current TOPOLOGIX approach using ESM-2 protein language model embeddings, which achieves AUROC 0.804 +/- 0.025 on the same benchmark while covering 100% of mutations versus about 18% for structure-limited tools. These are decisive tests of hypotheses, including negative results reported directly rather than reframed. This is the standard of scientific excellence EMBO's DORA/CoARA-aligned evaluation expects. CHECKLIST - [ ] Confirm PhD eligibility status with EMBO before drafting full application - [ ] Secure a host laboratory in an EMBO member state; confirm the lab has not submitted another application for the same selection round - [ ] Obtain a formal letter of support from the host laboratory principal investigator - [ ] Request endorsement letters from Kent Berridge, Samuel Gershman, Nathaniel Daw, and Marcelo Mattar - [ ] Verify that all three CCT preprints are uploaded to OSF/Zenodo with DOIs - [ ] Verify the status of the three journal submissions (IART, PNPBP, NBR) and the Alcohol co-authored paper - [ ] Prepare a two-page CV in EMBO format, including ORCID and GitHub - [ ] Draft the full research proposal using the CCT model as the core, with the three aims specified in the research statement - [ ] Prepare a budget breakdown for salary, relocation, and family support - [ ] Confirm the rolling deadline and the specific submission portal requirements - [ ] Check whether a PhD certificate or proof of enrollment in a PhD programme is required at the time of application - [ ] Verify that the host country qualifies as a new host country under EMBO mobility rules EDITOR NOTES - Eligibility risk: EMBO Postdoctoral Fellowships require a PhD or equivalent doctoral degree. Eniola is enrolled in an M.Sc. and does not yet hold a PhD. The application must clarify his path to a PhD, either through enrollment in a PhD programme or a statement that the PhD is expected imminently. This is the single largest risk to the application. - The CCT model is the correct research line to lead with, as it is the most mature, externally validated, and directly aligned with EMBO's life sciences mandate. The TOPOLOGIX and neurocascade lines are strong but less developed and less aligned with EMBO's focus. - The endorsements from Berridge, Gershman, Daw, and Mattar are named in the profile, but the application must confirm that these researchers are willing to write formal letters of support. The profile lists them as collaborators or endorsers, but the letters themselves are not confirmed. - The host laboratory is not yet identified. The application cannot be submitted without a confirmed host lab in an EMBO member state. This is a required next step before drafting the full proposal. - The ergofluids line is explicitly a methods-validation project with a failed real-data gate. It should not be presented as validated or as a venture. It is not part of this application and should not appear in the research statement. - The psyche-twin project is a personal knowledge-graph architecture. It is not a life sciences research line and should not appear in the EMBO application. - The profile lists employment at Synthcare starting March 2026. The application should clarify whether this is a full-time role that would conflict with a fellowship start date.