ASCEND
BY NTHRYS

NTHRYS › Internships

Ai Retrosynthesis For Pharma

Ai Retrosynthesis For Pharma
Category
Focused area
Variant
Pay · Join
Step 2 of 5Choose category
Field
▾
Category
▾
Focused area
▾

Ai Retrosynthesis For Pharma

Choose a category below to begin. Each category opens into focused areas, and selecting a focused area lets you pick your final internship variant (your preferred track, mode and duration).

Internship Types — tap to learn more
Mode — tap to learn more
Duration — tap to learn more
🔍

Showing 1–20 of 50

AI Computer-Aided Retrosynthesis Research
Internship planning synthesis routes with computer-aided AI that ranks by feasibility and cost. Applied sessions reinforce each technique.
5 focused areasClick to view more details →
Machine Learning for Route Feasibility Prediction
Internship predicting route feasibility with ML before chemists commit reagents and weeks. Interns practise on genuine research problems.
5 focused areasClick to view more details →
AI Protecting Group Strategy Automation Research
Internship automating protecting group strategy with AI that minimises steps and side reactions. Interns work with realistic case datasets.
5 focused areasClick to view more details →
Deep Learning for Chiral Synthesis Planning
Internship planning chiral synthesis with deep models that preserve stereochemistry through routes. Hands-on work runs alongside theory modules.
5 focused areasClick to view more details →
AI Flow Chemistry Retrosynthesis Research
Internship planning flow-compatible routes with AI that favours continuous, safer transformations. Guided practice with real datasets throughout.
5 focused areasClick to view more details →
AI API Synthesis Cost Optimization Research
Internship optimising active ingredient synthesis cost with AI route comparison across suppliers. Hands-on work runs alongside theory modules.
5 focused areasClick to view more details →
AI Biocatalytic Retrosynthesis Research
Internship planning biocatalytic routes with AI retrosynthesis that inserts enzymes where they win. Interns practise on genuine research problems.
5 focused areasClick to view more details →
AI Reaction Template Mining Research
Internship mining reaction templates from literature with AI that builds usable synthesis rules. Mentor-led sessions build applied skill.
5 focused areasClick to view more details →
AI Green Retrosynthesis Strategy Research
Internship planning greener routes with AI scoring of solvent, waste, and energy at every step. Includes mentored hands-on analysis sessions.
5 focused areasClick to view more details →
AI Patent-Aware Retrosynthesis Planning Research
Internship planning routes with AI awareness of patent space so freedom to operate is preserved. Practical exercises anchor every concept taught.
5 focused areasClick to view more details →
Neural Network Reaction Outcome Prediction
Research developing graph neural networks to predict product distributions and selectivity in multi-step pharmaceutical syntheses.
5 focused areasClick to view more details →
Molecular Graph Representation Learning
Internship focused on creating and optimizing molecular graph embeddings for improved retrosynthesis model accuracy and efficiency.
5 focused areasClick to view more details →
AI Reagent and Catalyst Selection
Research project optimizing machine learning models to automatically recommend optimal reagents and catalysts for each synthetic step.
5 focused areasClick to view more details →
Retrosynthesis Reaction Tree Search Algorithms
Developing and benchmarking advanced tree search algorithms including Monte Carlo and reinforcement learning approaches for retrosynthetic planning.
5 focused areasClick to view more details →
Transformer Models for Sequence Synthesis
Research implementing and fine-tuning transformer-based models to generate sequential synthetic routes from molecular targets.
5 focused areasClick to view more details →
Chemical Reaction Data Curation Automation
Internship developing automated quality control systems for large-scale pharmaceutical reaction databases used in AI model training.
5 focused areasClick to view more details →
Synthesis Yield Prediction Machine Learning
Research building predictive models to estimate reaction yields based on structural features and reaction conditions in pharmaceutical syntheses.
5 focused areasClick to view more details →
Retro-biosynthetic Pathway Integration Research
Exploring AI methods to combine traditional retrosynthesis with enzymatic and microbial fermentation pathways for hybrid pharmaceutical production.
5 focused areasClick to view more details →
Real-time Synthetic Route Optimization Engine
Developing dynamic optimization algorithms that rank and refine multiple synthetic routes based on cost, time, and safety metrics.
5 focused areasClick to view more details →
AI-Driven Scale-up Synthesis Planning
Research investigating how machine learning predicts scalability challenges and optimizes procedures for translating laboratory routes to manufacturing.
5 focused areasClick to view more details →