Back to search
AI Robotix Linkedin · Posted 16d ago

We are looking for AI engineers who want to cure diseases — not just write code.

Tohatchi

Linkedin
Continue to application Add your email once, then Caio opens the original posting.

Indexed description

AI Robotix Biotech Intelligence

We believe AI must serve life.

Human-centered biotech intelligence

Its greatest promise is to profoundly transform human health by accelerating scientific discovery, anticipating disease, personalizing treatments, and opening new possibilities to improve the quality of life for humanity.

A control room for disease reasoning

Integrated modules that perceive biology, propose interventions, and reason from mechanism to patient impact.

Disease-state map active

Predicted downstream effects

Mechanism-awarePathway impactConfidence trail

Reasoning Pulse

Perturbation Reasoning

Disease State Map

Mechanism, pathway, and patient-state canvas

Active

Layers

Pathways

Proteins

Cells

Genomics

Patient State

Tissue Inflammation

Candidate state

Predicted downstream effects

Mechanism-awarePathway impactConfidence trail

Patient Cohort View

n = 1,204

Therapeutic Hypothesis Engine

Templates intervention logic, predicts outcomes, and prioritizes promising therapeutic options.

Perturbation Reasoning

Explores perturbations to predict mechanism-aware effects and downstream consequences.

Modality Pathways

Maps antibodies, small molecules, RNA, protein engineering, cell-state modulation, and combinations.

Evidence Graph

Connects literature, datasets, and experiments with confidence scoring and provenance.

Human Translation

Bridges mechanisms to patient relevance through biomarkers, endpoints, experiments, and real-world data.

Hypothesis to Proof

Understand

Define the biological question and context.

Hypothesize

Generate mechanism-grounded hypotheses.

Perturb

Design experiments and in silico screens.

Design

Prioritize and refine best interventions.

Validate

Test, confirm, and analyze outcomes.

Prove

Advance with confidence to patient impact.

A control room for disease reasoning

Integrated modules that perceive biology, propose interventions, and reason from mechanism to patient impact.

Disease-state map active

Predicted downstream effects

Mechanism-awarePathway impactConfidence trail

Disease State Map

Central reasoning canvas

Predicted downstream effects

Mechanism-awarePathway impactConfidence trail

Therapeutic Hypothesis Engine

Templates intervention logic, predicts outcomes, and prioritizes promising therapeutic options.

Perturbation Reasoning

Explores perturbations to predict mechanism-aware effects and downstream consequences.

Modality Pathways

Maps antibodies, small molecules, RNA, protein engineering, cell-state modulation, and combinations.

Evidence Graph

Connects literature, datasets, and experiments with confidence scoring and provenance.

Human Translation

Bridges mechanisms to patient relevance through biomarkers, endpoints, experiments, and real-world data.

Hypothesis to Proof

Understand

Define the biological question and context.

Hypothesize

Generate mechanism-grounded hypotheses.

Perturb

Design experiments and in silico screens.

Design

Prioritize and refine best interventions.

Validate

Test, confirm, and analyze outcomes.

Prove

Advance with confidence to patient impact.

Biological Drivers

Cell States

Patient Subtypes

Pillar 01

Disease intelligence before drug design.

Before designing therapies, we map disease states, biological drivers, patient subtypes, and intervention opportunities. The goal is not just to find targets, but to understand where intervention could matter.

Disease states

Biological drivers

Patient subtypes

Pillar 02

From biological complexity to therapeutic hypotheses.

The platform translates disease-state understanding into structured hypotheses: what to perturb, why it matters, what result is expected, and which therapeutic modalities may be plausible.

Pillar 03

Designed for validation, not just prediction.

Each hypothesis must move toward experimental and translational proof: biomarkers, assays, model systems, patient-relevant endpoints, and evidence packages that make the next decision clearer.

“The next breakthrough will come from systems that understand disease before they design the drug.”

Explore Our Tech Read the Insights

Disease intelligence, therapeutic hypothesis generation, and translational validation design.

Company

Our MissionOur TechInsights

Platform

Disease IntelligenceTherapeutic HypothesesTranslational Validation

Legal

PrivacyTerms

Contact

EmailLinkedInX / Twitter

© 2026 AI Robotix. All rights reserved.

Disease understanding before drug design.

Free. 20 seconds. No password. See every match in this search.

Create a free Caio profile to unlock more results and save your role and location preferences.

Unlock free search
Want help applying to roles like this? Search Caio for free. If repetitive applications get heavy, Managed Job Search adds supervised execution for $99/month.
View Managed Job Search