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Bayesian Optimization Jobs in North Carolina (NOW HIRING)

Design and deploy closed‑loop learning systems using methods including Bayesian optimisation, model predictive control, reinforcement learning and active learning to guide experimental campaigns in ...

New

Data Scientist

Raleigh, NC · On-site

$110 - $170/hr

Apply classical statistical methods (GLMs, GAMs, mixed-effects models, Bayesian inference ... Databricks ML Ecosystem ATS Optimization KeywordsHard Skills * Statistical Methods * Machine ...

New

... optimal quality. * Provide statistical consultancy support to sponsors across the full span of ... Experience of Bayesian approaches to design and analysis of clinical data preferred. * Experience ...

Expertise in mathematical methodologies, specifically for developing and testing optimization algorithms with Bayesian methodologies, neural networks, and frequentist models. Data Management and ...

Bayesian Optimization information

What is the difference between Bayesian Optimization vs Data Scientist?

AspectBayesian OptimizationData Scientist
Primary FocusOptimizing complex functions and hyperparametersAnalyzing data, building models, deriving insights
Required SkillsStatistics, probability, machine learning, programmingStatistics, programming, data analysis, visualization
Work EnvironmentResearch labs, AI/ML teams, R&D departmentsBusiness, tech companies, consulting firms
Common ToolsPython, R, Bayesian libraries (e.g., GPy, scikit-optimize)Python, R, SQL, visualization tools

Bayesian Optimization is a specialized technique used within machine learning and AI to efficiently tune hyperparameters or optimize functions. Data Scientists often utilize Bayesian Optimization as part of their toolkit but have broader responsibilities, including data analysis, modeling, and reporting. While Bayesian Optimization focuses on optimization tasks, Data Scientists work on understanding and interpreting data to inform business decisions.

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What cities in North Carolina are hiring for Bayesian Optimization jobs? Cities in North Carolina with the most Bayesian Optimization job openings:
Infographic showing various Bayesian Optimization job openings in North Carolina as of August 2026, with employment types broken down into 1% Internship, 86% Full Time, 8% Part Time, and 5% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Principal Machine Learning Scientist

NCBiotech

Durham, NC • On-site

$180 - $260/hr

Other

Medical, Dental, Vision

Posted 3 days ago

New


Job description

Principal Machine Learning Scientist

RTP, NC - Hybrid | Full-Time

The mission

CellForge is an AI-guided robotic platform for scalable, reproducible human cell manufacturing. We combine single-cell transcriptomics, imaging, and robotic culture systems with machine learning to discover and implement optimal differentiation protocol, and close the loop between what the cells tell us and what we do next.

The role

You will build the intelligence layer: models that listen to cells, predict where they're going, and actively steer them toward target states. This is a hands‑on principal‑level IC role reporting directly to the CEO.

Core work
  • Design and deploy closed‑loop learning systems using methods including Bayesian optimisation, model predictive control, reinforcement learning and active learning to guide experimental campaigns in real time
  • Build multimodal models across single‑cell RNA‑seq, imaging, time‑series sensor data, and experimental metadata
  • Develop trajectory‑aware dynamics models for cell fate prediction and protocol optimisation
  • Define data pipelines and ML infrastructure for high‑throughput biological experimentation
  • Work directly with biologists and automation engineers to translate biological questions into tractable ML problems
What we're looking forRequired
  • Strong ML fundamentals - probabilistic modelling, optimisation, experimental design
  • Hands‑on experience with biological data, especially scRNA‑seq (scanpy, anndata, scVI etc); imaging processing is a plus
  • Proficiency in Python and PyTorch (or equivalent)
  • Demonstrated ability to ship models in complex, real‑world settings with noisy, sparse data
  • PhD or equivalent practical depth in ML, computational biology, bioinformatics, or related field
Preferred
  • Experience with closed‑loop or real‑time learning systems
  • Prior biotech / scientific ML work
  • Experience in an early‑stage company environment
  • Publications in top domain‑relevant journals
What we offer
  • Ground‑floor ML ownership at a seed‑stage deep tech company
  • We pay a real salary - just below market - and weight the rest toward meaningful equity. Ideal if you're excited to build long‑term value with us.
  • Direct access to founders and the full experimental platform - you see the data you generate
  • High autonomy, fast pace, real biological impact
  • Excellent medical benefits, dental, eyecare, and more
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