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Research Services
Accelerate your R&D
We apply the latest machine learning methods and software tools to partner with you in computational science. From large language models to dynamical system modeling, we can help fast track your research.
  • Deliver scientific outcomes faster by working with our experts in computational sciences.
  • Reduce uncertainty in high-risk R&D initiatives by leveraging our industry experience.
  • Keep up to date with the latest applications of machine learning.
  • Up-level your team through collaboration with our experts.

Manifold’s contribution has been invaluable. Our integration of machine learning algorithms will enable the dynamic adjustment of treatment...

Chief Medical Officer, Digital Therapeutic

Natural Language Processing


Fine-tune large language models to your enterprise use cases

Semantic Search

Search and text retrieval over large document corpuses

LLM-Enabled UI/UX

Human in the loop UI/UX for query generation, plotting, cohort building, and more

Virtual Assistant

Natural language interface to chat with a corpus of documents

Structure Extraction

Extract structured data from unstructured clinical text data

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Computer Vision

Image Processing

Process large-scale imaging data, including histology slides, CT, MRI, and video

Feature Engineering

Extract semantic features from images like nodule size or cell count

Synthetic Data

Use techniques from data centric AI to create more training data for machine learning

Semantic Segmentation

Segment images from your instruments, from fluorescence microscopes to CT scans

Multimodal Prediction

Forecast disease progression or response to treatment by combining genotype and imaging data.

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Time Series

Digital Biomarkers

Develop digital biomarkers from multivariate time series data

Longitudinal Prediction

Predict disease risk or adherence from longitudinal patient data sources

Bayesian Modeling

Probabilistic time series modeling for forecasting and anomaly detection

Signal Processing

Discrete-time signal processing for linear and non-linear systems

System Identification

Dynamical system system identification using deep learning

Anomaly Detection

Unsupervised techniques to find anomalous patterns in time series data

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Analyze genotypes and downstream traits to find associations for disease, drug response, or clinical outcome

Diagnostic Biomarkers

Find biomarkers from NGS data to classify patients and develop companion diagnostics

Next Gen Sequencing

Process fastq files from NGS to do alignment, count transcripts, call variants, and more

Predictive Biomarkers

Predict which patients are more likely to reach primary or secondary clinical endpoints

Generative AI

Use state-of-the-art generative AI models to predict molecular structures or binding

Causal Inference

Estimate causal effects from observational data using DAGs and modern inference techniques

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Case Studies

Multiomics Companion Diagnostic

Discovered novel multiomic biomarkers using parallelized machine learning pipelines.

How Can We Help?

We are a multi-disciplinary team focused on developing scientific insights using a mix of applied mathematics, machine learning, and computing.

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