Job Opportunities API

# Nutrition Experts — Planning AI Project ## 🏢 About Vetto Vetto is a global platform that connects top-tier professionals to strategic Artificial Intelligence projects around the world. Our mission is to build trust, quality, and long-term value within the AI ecosystem, for both exceptional talent and companies operating at the forefront of technology. ## 📖 About the project We're recruiting nutrition experts to review and improve real-world scenarios used to train AI planning assistants in a clinical and educational context. The AI model will act as a nutrition tutor — structuring dietary problems, mapping decision trees, and teaching evidence-based reasoning to students and healthcare professionals. Your job is to think like a senior nutritionist: break down clinical or dietary challenges, identify alternatives, justify decisions with concrete data, and ensure the reasoning is both rigorous and clear enough to teach. ## 👤 Who can apply Professionals from any nutrition specialty — clinical, sports, hospital, eating behavior, pediatric, oncological, or community nutrition. Anyone with hands-on experience diagnosing nutritional problems and making evidence-based decisions. Final-year undergraduate students in nutrition or dietetics with practical clinical experience are also welcome to apply. ## 🔍 Specialties we're looking for We are especially interested in professionals with expertise in one or more of the following areas: - Clinical Nutrition (outpatient or inpatient) - Sports Nutrition - Hospital / Critical Care Nutrition - Eating Behavior & Nutritional Psychology - Pediatric Nutrition - Oncological Nutrition - Community / Public Health Nutrition - Functional Nutrition ## 🧩 Selection In this application, you will answer questions following the instructions below. If selected, you will be invited to review real nutrition case scenarios as part of the project. For the reasoning case, present a real nutritional problem you diagnosed or solved — a dietary assessment challenge, clinical intervention decision, micronutrient deficiency investigation, eating behavior issue, sports performance adjustment, etc. You may anonymize it. We are not evaluating whether your conclusion was right. We are evaluating how you think. ⚠️ This is just an illustrative example. Your application should include more detail, specific data points, and thorough reasoning for each discarded alternative. The case is structured in 4 parts: Part 1 — The Problem: describe the nutritional problem and what data or information you had available at the start (anthropometric data, lab results, dietary recall, clinical history, etc.). Part 2 — Your Journey: describe your reasoning in 3 steps. For each step, explain what you analyzed or decided and what specific metric, data point, or clinical finding drove that decision. Part 3 — Discarded Alternatives: for each of the 3 steps, list at least 2 hypotheses you considered but ruled out and explain what concrete data eliminated each one. “It wasn’t the case” is not a valid answer. Part 4 — Conclusion: describe the final nutritional recommendation or intervention and how the evidence you gathered led to it. Also highlight 1–2 key insights — the most important findings or turning points in your reasoning: a lab marker that confirmed your direction, a detail that ruled out a strong alternative, or a non-obvious observation that most practitioners would have missed. Example: Part 1 — The Problem A 34-year-old female recreational runner came in reporting persistent fatigue and declining performance over the past 3 months. BMI was 21.4. She trained 5x/week and reported eating “healthy.” No obvious dietary restriction reported. Part 2 — Your Journey Step 1: Requested a full blood panel — ferritin came back at 8 ng/mL (well below the 20 ng/mL threshold for athletes), while hemoglobin was still within normal range at 12.1 g/dL. This