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Chemiinformatics

Chemiinformatics
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Chemiinformatics

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).

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Showing 1–20 of 50

AI Molecular Descriptor Development Research
Internship developing molecular descriptors with AI representations that outperform classical sets. Includes mentored hands-on analysis sessions.
5 focused areasClick to view more details →
Machine Learning Chemical Property Prediction
Internship predicting chemical properties with ML models benchmarked against measured datasets. Applied sessions reinforce each technique.
5 focused areasClick to view more details →
AI Chemical Database Curation Research
Internship curating chemical databases with AI standardisation of structures, names, and duplicates. Interns practise on genuine research problems.
5 focused areasClick to view more details →
AI Reaction Informatics Research
Internship studying reaction informatics with AI mining of transformations, conditions, and yields. Mentor-led sessions build applied skill.
5 focused areasClick to view more details →
AI Toxicity Informatics Research
Internship applying informatics to toxicity with AI prediction across endpoints and species. Interns practise on genuine research problems.
5 focused areasClick to view more details →
AI Chemical Space Mapping Research
Internship mapping chemical space with AI methods that organise molecules by structure and property. Applied sessions reinforce each technique.
5 focused areasClick to view more details →
AI SMILES & Graph-Based Informatics Research
Internship studying molecular representations with AI models over string and graph encodings. Hands-on work runs alongside theory modules.
5 focused areasClick to view more details →
AI Quantum Chemical Informatics Research
Internship combining quantum calculation with informatics through AI models trained on results. Interns work with realistic case datasets.
5 focused areasClick to view more details →
AI Environmental Chemical Informatics Research
Internship applying informatics to environmental chemicals with AI prediction of fate and hazard. Guided practice with real datasets throughout.
5 focused areasClick to view more details →
AI Natural Product Informatics Research
Internship applying informatics to natural products with AI dereplication and activity linking. Practical exercises anchor every concept taught.
5 focused areasClick to view more details →
Deep Learning Drug Scaffold Optimization
Develop neural network models to predict and optimize molecular scaffolds for improved drug efficacy and safety profiles.
5 focused areasClick to view more details →
Generative Models Chemical Compound Design
Research generative adversarial networks and variational autoencoders to create novel chemical compounds with desired properties.
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Molecular Docking Algorithm Development
Implement and optimize computational docking algorithms to predict protein-ligand binding interactions and affinities.
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Chemical Fingerprinting Pattern Recognition
Investigate various chemical fingerprint representations and machine learning techniques for molecular similarity assessment and clustering.
5 focused areasClick to view more details →
Retrosynthetic Analysis AI Framework
Develop artificial intelligence systems to predict synthetic routes and disconnection strategies for target molecule synthesis.
5 focused areasClick to view more details →
Metabolite Prediction Neural Networks
Build deep learning models to predict drug metabolite formation and biotransformation pathways in biological systems.
5 focused areasClick to view more details →
Solubility Prediction Machine Learning
Train regression models using experimental and calculated molecular descriptors to accurately predict compound solubility.
5 focused areasClick to view more details →
Protein Structure Ligand Interaction Analysis
Apply structural bioinformatics and chemiinformatics techniques to analyze binding site geometry and ligand interaction patterns.
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Chemical Ontology Development Research
Design and implement semantic frameworks to organize and standardize chemical knowledge representation and classification.
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Pharmacophore Modeling Computational Methods
Develop computational pharmacophore models to identify essential functional groups and spatial arrangements for drug binding.
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