MOTIVATION LETTER The Wellcome Sanger Institute has built its reputation on decoding genomes to understand biology and disease. My research in computational neuroscience and pharmacology has followed a parallel path: decoding the neural and pharmacological mechanisms that drive addiction. The CCT model I developed and validated independently demonstrates that reward-memory consolidation can be prevented through a tripartite pharmacological framework, achieving an 85.8 percent reduction in encoding probability in ODE/RK45 simulations with Bayesian MCMC validation. This work required the same computational rigor that genomic analysis demands: Python-based modeling, statistical validation, and hypothesis-driven experimental design. My technical toolkit maps directly onto Sanger's needs. I build and validate predictive models using Python, PyMC for Bayesian inference, and topological data analysis via Ripser and Gudhi for high-dimensional biological data. The TOPOLOGIX platform I developed applies persistent homology and bipartite simplicial complexes to drug-protein interactions, with a working MVP for hERG cardiotoxicity screening. These methods transfer directly to genomic data analysis: variant effect prediction, population structure inference, and network-based interpretation of genetic interactions. I am applying to Sanger's early careers programme because I want to pivot my computational skills toward genomics while retaining my focus on addiction biology. Addiction has a strong genetic component, and Sanger's expertise in large-scale sequencing and functional genomics offers the infrastructure I need to investigate how genetic variation in dopamine receptor genes, opioid receptor genes, and reward pathway regulators modulates treatment response. My provisional patent on the CCT core architecture and my co-authored paper under review at Alcohol demonstrate that I can produce publishable work independently. At Sanger, I would apply the same rigor to genomic questions. Nigeria has one of the highest rates of substance use disorders in West Africa, yet genomic research capacity remains limited. I intend to return to Nigeria after training to establish a computational genomics group focused on addiction genetics in African populations. Sanger's commitment to global health and capacity building aligns directly with this goal. I am a computational pharmacologist who has built models, platforms, and a testable theory of addiction from first principles. Sanger's training environment is the right place to add genomics to that foundation. RESEARCH STATEMENT My independent research since 2025 has focused on a single question: can the encoding of reward memories be prevented pharmacologically before they become compulsive? The Conjunctive Consolidation Threshold model answers this question with a tripartite framework that targets three simultaneous mechanisms: NMDA receptor antagonism to block synaptic plasticity, beta-adrenergic blockade to prevent emotional salience tagging, and opioid receptor modulation to disrupt reward valuation. The model specifies that these three interventions must be applied within a narrow temporal window and at specific dose ratios to achieve super-additive effects. The formal mathematical specification of the CCT model, deposited on OSF, defines the encoding probability as a function of three coupled differential equations solved via Runge-Kutta 45 integration. The Bayesian population dynamics paper on Zenodo extends this to a hierarchical model that accounts for inter-individual variability in receptor expression and drug metabolism. All five pre-registered hypotheses H1 through H5 were confirmed. Encoding probability dropped from 0.855 to 0.122, a reduction of 85.8 percent. The super-additivity effect measured 12.8 percentage points above the sum of individual effects, confirming that the three interventions interact non-linearly. The platforms I built support this research. IMPRINT screens compounds for addiction liability using a multi-feature classifier trained on ADMET, QSAR, and receptor binding data. TOPOLOGIX applies topological data analysis to drug-protein interaction networks, identifying persistent homology features that correlate with off-target cardiotoxicity. GATE evaluates neural stimulation safety for BCI applications using conductance-based neuron models in NEURON and Brian2. These tools are all Apache 2.0 licensed and available on GitHub. At Sanger, I would apply these computational methods to genomic data. The CCT model identifies specific receptor targets; genomic analysis of those receptor genes in addiction cohorts could identify variants that predict treatment response. I would learn Sanger's sequencing pipelines, variant calling workflows, and functional genomics assays to design experiments that test CCT predictions in human genetic data. The Bayesian framework I use for population dynamics is directly applicable to polygenic risk score modeling and GWAS interpretation. My long-term research goal is to build a computational genomics group in Nigeria that focuses on addiction genetics in African populations. African genetic diversity is underrepresented in addiction genomics, and the CCT model's predictions have never been tested in African cohorts. Sanger's training would give me the technical foundation to design and lead those studies. SHORT ESSAY: WHY THIS PROGRAMME The Wellcome Sanger Institute is the world leader in genomic sequencing and functional genomics. Its early careers programme offers structured training in computational biology, bioinformatics, and genomic data analysis within a research environment that prioritizes scientific rigor and open science. My independent research has followed the same principles: all preprints are deposited on OSF and Zenodo with DOIs, all code is on GitHub under open licenses, and all hypotheses were pre-registered before analysis. Sanger's culture of reproducibility and data sharing matches my own practice. I need training in genomic analysis methods that I cannot access in Nigeria. Sanger offers hands-on experience with large-scale sequencing data, variant interpretation pipelines, and functional genomics assays. The programme's emphasis on computational skills aligns with my existing Python, R, and HPC workflow expertise. I would contribute my experience in Bayesian modeling, topological data analysis, and drug-target interaction prediction to Sanger's computational groups while learning genomic methods that I cannot teach myself from papers alone. The programme's rolling deadline allows me to apply now while I complete my MSc applications for October 2026. I am available to start as soon as the programme permits. SHORT ESSAY: CAREER GOALS My immediate goal is to gain formal training in genomics and computational biology at Sanger. Within one year, I aim to complete a project that applies topological data analysis or Bayesian modeling to a genomic dataset relevant to addiction or neuropharmacology. Within three years, I intend to enroll in a PhD programme in computational neuroscience or genomics, building on the skills and collaborations I develop at Sanger. My five-year goal is to establish an independent research group in Nigeria that focuses on addiction genetics in African populations. Nigeria has no dedicated computational genomics group for substance use disorders, despite having one of the highest prevalence rates in West Africa. I would combine the CCT model with genomic analysis to identify population-specific genetic variants that modulate addiction risk and treatment response. Sanger's training, network, and reputation would be essential for securing the funding and collaborations needed to build this group. In ten years, I aim to lead a pan-African consortium for addiction genomics, using the methods I learn at Sanger to address a public health crisis that disproportionately affects young Africans. CHECKLIST - [ ] Motivation letter, 300-500 words, tailored to Wellcome Sanger Institute early careers programme - [ ] Research statement, 400-600 words, describing CCT model, platforms, and genomic pivot - [ ] Short essay: Why this programme, 200-350 words - [ ] Short essay: Career goals, 200-350 words - [ ] CV in PDF format, including ORCID, GitHub, Zenodo/OSF links, publications, platforms, employment history - [ ] Academic transcripts from University of Ibadan (B.Pharm) - [ ] Proof of PCN pharmacist license - [ ] Two reference letters: one from a computational collaborator (e.g., Kent Berridge or Samuel Gershman), one from a pharmacology supervisor - [ ] Preprint links: OSF 10.17605/OSF.IO/KG7B5, OSF 10.17605/OSF.IO/EMY4U, Zenodo 10.5281/zenodo.20492472 - [ ] GitHub profile link: github.com/AmunRaPtah - [ ] Provisional patent documentation for CCT core architecture (Q3 2026) EDITOR NOTES - Eligibility risk: The Wellcome Sanger early careers programme typically targets recent graduates or those with limited post-degree experience. Eniola graduated in 2021 and has held three positions since, including a current role as National Product Manager. This may exceed the programme's definition of "early career." Verify the programme's specific eligibility criteria for years since graduation and number of prior positions. If needed, frame the product manager role as a temporary position taken to fund independent research, not as a career track. - Genomics pivot credibility: The application must convince reviewers that Eniola's computational skills genuinely transfer to genomics. The current draft emphasizes TDA and Bayesian modeling, but does not mention any prior work with sequencing data, variant calling, or genomic databases. Consider adding a sentence about any coursework, self-study, or small project involving genomic data (e.g., "I have completed the Sanger Institute's free online course on variant interpretation" or "I analyzed publicly available GWAS summary statistics for addiction phenotypes using my Bayesian pipeline"). - UK visa and relocation: Eniola is based in Lagos, Nigeria. The application does not address visa sponsorship, relocation timeline, or funding for travel and accommodation. The programme may not provide visa support or relocation stipends. Verify whether the programme offers these, and if not, Eniola must state his ability to self-fund relocation or secure external funding. - Reference letter logistics: Kent Berridge and Samuel Gershman are named as endorsers, but it is unclear whether they have agreed to write letters. Confirm with each before listing them as referees. If they decline, identify alternative referees from the collaborators list (Nathaniel Daw, Marcelo Mattar) or from the CDDDP and GHRU-GSAR research assistant roles. - MSc timeline conflict: Eniola is applying for MSc programmes starting October 2026. If Sanger's early careers programme requires a longer commitment or starts earlier, there may be a scheduling conflict. Clarify the programme's duration and start date, and state in the application whether Eniola can commit to the full programme before starting his MSc.