Draft — L’Oréal–UNESCO For Women in Science Sub-Saharan Africa Program 2026

MOTIVATION LETTER

The L’Oréal–UNESCO For Women in Science Sub-Saharan Africa Program supports early-career female scientists whose research addresses pressing regional challenges. My work sits precisely at that intersection: computational neuroscience applied to addiction, a growing public health crisis across Sub-Saharan Africa. The WHO estimates that fewer than 1 in 6 people with substance use disorders in Africa receive any form of treatment, and pharmacological interventions remain scarce. My research builds the quantitative foundation for better ones.

I am a Nigerian pharmacist and computational researcher, currently enrolled in the M.Sc. Digital Health program at the Hasso Plattner Institute, University of Potsdam. My primary research line, the Conjunctive Consolidation Threshold (CCT) model, is a tripartite pharmacological framework for reward-memory encoding prevention in addiction. It couples three axes: dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast, into a system of ordinary differential equations solved with RK45. I calibrated the model using Bayesian MCMC (PyMC DEMetropolisZ) with 14 free parameters and literature-elicited priors drawn from a systematic screen of 1,847 records. All five pre-registered hypotheses (H1-H5) were confirmed, with posterior super-additivity of 13-22 percentage points across model versions. Three sole-authored preprints are under review at peer-reviewed journals (IART, PNPBP, NBR), and a co-authored paper is under review at Alcohol (Elsevier).

The CCT model generates testable predictions about which drug combinations, at which doses and timing, could prevent the consolidation of reward memories that drive relapse. That is directly relevant to African populations, where polypharmacy and limited psychiatric infrastructure make precise, mechanism-based treatment design essential. My Bayesian calibration approach also addresses a known weakness in computational pharmacology: models that fit one dataset but fail on the next. By pre-registering hypotheses and reporting posterior distributions rather than point estimates, I am building a model that can be updated as new clinical data from African cohorts becomes available.

The program’s selection criteria emphasize scientific quality, innovation, and societal impact. The CCT model delivers on all three: it is the first framework to explicitly model the conjunctive threshold at which reward memories consolidate, it uses modern Bayesian methods to quantify uncertainty, and it targets a condition that destroys lives and economies across the region. I am applying for the €15,000 fellowship to support the next phase: fitting the circuit-layer parameters to real behavioral data and preparing a clinical translation protocol for review by African ethics boards.

I am a female scientist from Nigeria, early in my career, with a track record of independent, rigorous research. The L’Oréal–UNESCO program’s commitment to visibility for women in science matters to me personally; I have published under my own name, presented negative results honestly, and built my research program without a permanent institutional lab. This fellowship would provide not only funding but the recognition that helps independent researchers secure institutional partnerships. I am ready to contribute to the community of African women scientists and to serve as a visible example that rigorous computational research can be done from anywhere, including Lagos and Potsdam.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold (CCT) model addresses a specific, unanswered question in addiction neuroscience: what is the minimal set of concurrent neurochemical conditions required for a reward memory to consolidate, and can pharmacological intervention disrupt that conjunction? Current treatments target single receptors or transporters. Relapse rates remain above 60% within one year. The CCT model argues that consolidation requires simultaneous activity across three axes: dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast (the emotional valence difference between the drug state and the baseline state). Interrupting any one axis may be insufficient; interrupting the conjunction may be necessary and sufficient.

The model is implemented as a system of coupled ODEs solved with RK45, with parameters estimated via Bayesian MCMC. I screened 1,847 records from the literature to elicit priors for 14 free parameters, covering receptor binding kinetics, synaptic plasticity time constants, and affective state dynamics. The model was pre-registered with five hypotheses (H1-H5) before calibration. All five were confirmed. The key result is super-additivity: combined interventions across the three axes reduce consolidation probability by 13-22 percentage points more than the sum of individual effects. This is a genuine conjunctive threshold, not a trivial additive effect. The model predicts that a triple-therapy approach, targeting dopamine D2, NMDAR, and affective state (e.g., via GABA-A modulation), could prevent reward-memory consolidation at doses below those that produce individual side effects.

The next phase, which this fellowship would fund, has three components. First, I will fit the circuit-layer parameters to real behavioral data. My current neurocascade engine, a receptor-to-behavior simulation pipeline with coupled pharmacokinetic, receptor-binding, Wilson-Cowan circuit, and behavioral-readout layers, is already Bayesian-calibrated for mu-opioid, D2 dopamine, and GABA-A systems, with 62 of 62 tests passing. The circuit-layer parameters are currently labeled illustrative; fitting them to published rodent self-administration data will convert the CCT model from a pharmacological framework into a behavioral predictor. Second, I will extend the model to model human pharmacokinetic variability using African population data, where CYP2D6 and CYP3A4 polymorphisms differ significantly from European cohorts. Third, I will prepare a clinical translation protocol for review by African ethics boards, identifying candidate drug combinations that meet the conjunctive threshold criteria and are already approved for other indications.

The CCT model is methodologically rigorous by design. I pre-registered all hypotheses before calibration, reported posterior distributions rather than point estimates, and made all code and data publicly available on GitHub and OSF. This transparency is consistent with the L’Oréal–UNESCO program’s emphasis on scientific quality. It also addresses a real gap: computational models in psychiatry are rarely tested against the standard of pre-registered, falsifiable predictions. My model is.

The societal impact is direct. Substance use disorders in Sub-Saharan Africa are under-treated and under-studied. The CCT model offers a mechanism-based path to combination therapies that could be deployed in primary care settings, where specialized psychiatric services are scarce. It also provides a framework for evaluating traditional pharmacopeias: if a plant-derived compound modulates one of the three axes, the model can predict whether it is likely to contribute to consolidation prevention. This is a concrete, testable contribution to African health.

I am requesting the €15,000 fellowship to support: (1) compute time for the behavioral-data fits, (2) travel to a collaborating lab for validation experiments, and (3) open-access publication fees for the three manuscripts currently under review. I am an independent researcher; this funding would be the difference between continuing at my current pace and accelerating toward clinical translation.

EDITOR NOTES

- Research line selected: CCT model. This is the only line that directly matches the program’s life-sciences focus and its emphasis on societal impact in Africa. TOPOLOGIX is strong but is protein ML with no direct addiction or African health angle. The hERG and resistance topology studies are negative results and would not serve as the primary frame for a fellowship application. neurocascade is a supporting tool, not the primary research question. ergofluids is behind a validation gate and is methods-validation, not health-impact. psyche-twin is a personal knowledge-graph venture with no health or Africa angle. The CCT model is the best fit because it is health-relevant, Africa-relevant, methodologically rigorous, and at a stage where funding accelerates a clear next step.

- Eligibility risk: The program requires affiliation with a recognized university or research institution in Africa. The applicant is currently enrolled at HPI/Potsdam and is an independent researcher. This must be verified. If the program strictly requires African institutional affiliation, the applicant must secure a visiting researcher position at a Nigerian university (e.g., University of Ibadan, her alma mater) before applying. This is the single biggest risk to the application.

- Eligibility risk: The program targets PhD students (at least 2nd year) or postdoctoral researchers. The applicant is enrolled in an M.Sc. program and is pre-PhD. This must be checked against the program’s actual eligibility text. If M.Sc. students are ineligible, the applicant should either (a) apply as an independent researcher with a strong publication record, or (b) wait until the M.Sc. converts to a PhD track, or (c) contact the program directly to ask whether her three sole-authored preprints under review qualify her as an early-career researcher.

- Facts to verify: The applicant’s age (29) and the program’s age limit, if any. The CGPA conversion to German 1.9 should be verified with a formal conversion service if the program asks for transcripts. The three journals (IART, PNPBP, NBR) should be confirmed as peer-reviewed and not predatory. The Alcohol (Elsevier) co-authored paper status should be confirmed as under review.

- Gaps for applicant to fill: The motivation letter and research statement do not name a specific African institution or mentor. The applicant must add a named affiliation or collaboration in Africa (e.g., a professor at University of Ibadan willing to host her). The applicant must also add a specific budget breakdown for the €15,000, as the program may require it. The applicant must confirm whether the program requires a recommendation letter and, if so, from whom (Kent Berridge, Samuel Gershman, Nathaniel Daw, or Marcelo Mattar are all possible).

- Tone check: The letters avoid all banned phrases. The motivation letter opens with the program name and the research problem, not with "I." The research statement opens with the research question. Every sentence contains a concrete fact, number, or named claim. No em dashes used. No markdown formatting used.

MOTIVATION LETTER

The L’Oréal–UNESCO For Women in Science Sub-Saharan Africa Program supports early-career female scientists whose research addresses pressing regional challenges. My work sits precisely at that intersection: computational neuroscience applied to addiction, a growing public health crisis across Sub-Saharan Africa. The WHO estimates that fewer than 1 in 6 people with substance use disorders in Africa receive any form of treatment, and pharmacological interventions remain scarce. My research builds the quantitative foundation for better ones.

I am a Nigerian pharmacist and computational researcher, currently enrolled in the M.Sc. Digital Health program at the Hasso Plattner Institute, University of Potsdam. My primary research line, the Conjunctive Consolidation Threshold (CCT) model, is a tripartite pharmacological framework for reward-memory encoding prevention in addiction. It couples three axes: dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast, into a system of ordinary differential equations solved with RK45. I calibrated the model using Bayesian MCMC (PyMC DEMetropolisZ) with 14 free parameters and literature-elicited priors drawn from a systematic screen of 1,847 records. All five pre-registered hypotheses (H1-H5) were confirmed, with posterior super-additivity of 13-22 percentage points across model versions. Three sole-authored preprints are under review at peer-reviewed journals (IART, PNPBP, NBR), and a co-authored paper is under review at Alcohol (Elsevier).

The CCT model generates testable predictions about which drug combinations, at which doses and timing, could prevent the consolidation of reward memories that drive relapse. That is directly relevant to African populations, where polypharmacy and limited psychiatric infrastructure make precise, mechanism-based treatment design essential. My Bayesian calibration approach also addresses a known weakness in computational pharmacology: models that fit one dataset but fail on the next. By pre-registering hypotheses and reporting posterior distributions rather than point estimates, I am building a model that can be updated as new clinical data from African cohorts becomes available.

The program’s selection criteria emphasize scientific quality, innovation, and societal impact. The CCT model delivers on all three: it is the first framework to explicitly model the conjunctive threshold at which reward memories consolidate, it uses modern Bayesian methods to quantify uncertainty, and it targets a condition that destroys lives and economies across the region. I am applying for the €15,000 fellowship to support the next phase: fitting the circuit-layer parameters to real behavioral data and preparing a clinical translation protocol for review by African ethics boards.

I am a female scientist from Nigeria, early in my career, with a track record of independent, rigorous research. The L’Oréal–UNESCO program’s commitment to visibility for women in science matters to me personally; I have published under my own name, presented negative results honestly, and built my research program without a permanent institutional lab. This fellowship would provide not only funding but the recognition that helps independent researchers secure institutional partnerships. I am ready to contribute to the community of African women scientists and to serve as a visible example that rigorous computational research can be done from anywhere, including Lagos and Potsdam.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold (CCT) model addresses a specific, unanswered question in addiction neuroscience: what is the minimal set of concurrent neurochemical conditions required for a reward memory to consolidate, and can pharmacological intervention disrupt that conjunction? Current treatments target single receptors or transporters. Relapse rates remain above 60% within one year. The CCT model argues that consolidation requires simultaneous activity across three axes: dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast (the emotional valence difference between the drug state and the baseline state). Interrupting any one axis may be insufficient; interrupting the conjunction may be necessary and sufficient.

The model is implemented as a system of coupled ODEs solved with RK45, with parameters estimated via Bayesian MCMC. I screened 1,847 records from the literature to elicit priors for 14 free parameters, covering receptor binding kinetics, synaptic plasticity time constants, and affective state dynamics. The model was pre-registered with five hypotheses (H1-H5) before calibration. All five were confirmed. The key result is super-additivity: combined interventions across the three axes reduce consolidation probability by 13-22 percentage points more than the sum of individual effects. This is a genuine conjunctive threshold, not a trivial additive effect. The model predicts that a triple-therapy approach, targeting dopamine D2, NMDAR, and affective state (e.g., via GABA-A modulation), could prevent reward-memory consolidation at doses below those that produce individual side effects.

The next phase, which this fellowship would fund, has three components. First, I will fit the circuit-layer parameters to real behavioral data. My current neurocascade engine, a receptor-to-behavior simulation pipeline with coupled pharmacokinetic, receptor-binding, Wilson-Cowan circuit, and behavioral-readout layers, is already Bayesian-calibrated for mu-opioid, D2 dopamine, and GABA-A systems, with 62 of 62 tests passing. The circuit-layer parameters are currently labeled illustrative; fitting them to published rodent self-administration data will convert the CCT model from a pharmacological framework into a behavioral predictor. Second, I will extend the model to model human pharmacokinetic variability using African population data, where CYP2D6 and CYP3A4 polymorphisms differ significantly from European cohorts. Third, I will prepare a clinical translation protocol for review by African ethics boards, identifying candidate drug combinations that meet the conjunctive threshold criteria and are already approved for other indications.

The CCT model is methodologically rigorous by design. I pre-registered all hypotheses before calibration, reported posterior distributions rather than point estimates, and made all code and data publicly available on GitHub and OSF. This transparency is consistent with the L’Oréal–UNESCO program’s emphasis on scientific quality. It also addresses a real gap: computational models in psychiatry are rarely tested against the standard of pre-registered, falsifiable predictions. My model is.

The societal impact is direct. Substance use disorders in Sub-Saharan Africa are under-treated and under-studied. The CCT model offers a mechanism-based path to combination therapies that could be deployed in primary care settings, where specialized psychiatric services are scarce. It also provides a framework for evaluating traditional pharmacopeias: if a plant-derived compound modulates one of the three axes, the model can predict whether it is likely to contribute to consolidation prevention. This is a concrete, testable contribution to African health.

I am requesting the €15,000 fellowship to support: (1) compute time for the behavioral-data fits, (2) travel to a collaborating lab for validation experiments, and (3) open-access publication fees for the three manuscripts currently under review. I am an independent researcher; this funding would be the difference between continuing at my current pace and accelerating toward clinical translation.

EDITOR NOTES

- Research line selected: CCT model. This is the only line that directly matches the program’s life-sciences focus and its emphasis on societal impact in Africa. TOPOLOGIX is strong but is protein ML with no direct addiction or African health angle. The hERG and resistance topology studies are negative results and would not serve as the primary frame for a fellowship application. neurocascade is a supporting tool, not the primary research question. ergofluids is behind a validation gate and is methods-validation, not health-impact. psyche-twin is a personal knowledge-graph venture with no health or Africa angle. The CCT model is the best fit because it is health-relevant, Africa-relevant, methodologically rigorous, and at a stage where funding accelerates a clear next step.

- Eligibility risk: The program requires affiliation with a recognized university or research institution in Africa. The applicant is currently enrolled at HPI/Potsdam and is an independent researcher. This must be verified. If the program strictly requires African institutional affiliation, the applicant must secure a visiting researcher position at a Nigerian university (e.g., University of Ibadan, her alma mater) before applying. This is the single biggest risk to the application.

- Eligibility risk: The program targets PhD students (at least 2nd year) or postdoctoral researchers. The applicant is enrolled in an M.Sc. program and is pre-PhD. This must be checked against the program’s actual eligibility text. If M.Sc. students are ineligible, the applicant should either (a) apply as an independent researcher with a strong publication record, or (b) wait until the M.Sc. converts to a PhD track, or (c) contact the program directly to ask whether her three sole-authored preprints under review qualify her as an early-career researcher.

- Facts to verify: The applicant’s age (29) and the program’s age limit, if any. The CGPA conversion to German 1.9 should be verified with a formal conversion service if the program asks for transcripts. The three journals (IART, PNPBP, NBR) should be confirmed as peer-reviewed and not predatory. The Alcohol (Elsevier) co-authored paper status should be confirmed as under review.

- Gaps for applicant to fill: The motivation letter and research statement do not name a specific African institution or mentor. The applicant must add a named affiliation or collaboration in Africa (e.g., a professor at University of Ibadan willing to host her). The applicant must also add a specific budget breakdown for the €15,000, as the program may require it. The applicant must confirm whether the program requires a recommendation letter and, if so, from whom (Kent Berridge, Samuel Gershman, Nathaniel Daw, or Marcelo Mattar are all possible).

- Tone check: The letters avoid all banned phrases. The motivation letter opens with the program name and the research problem, not with "I." The research statement opens with the research question. Every sentence contains a concrete fact, number, or named claim. No em dashes used. No markdown formatting used.

AI Draft — L’Oréal–UNESCO For Women in Science Sub-Saharan Africa Program 2026