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1–2 jobs· newest first

Postdoctoral Research Associate, AI/ML for Chemical Reactions and AutomationNew
Oak Ridge National Laboratory · Oak Ridge, US
Full-time · Associate
Staff Data Scientist Reinforcement Learning – Offer Intelligence (m/f/d)New
SIXT · Lisbon, Portugal
Hybrid · Staff

+10K new in the last hour

Postdoctoral Research Associate, AI/ML for Chemical Reactions and Automation

Oak Ridge National Laboratory · Posted Nov 10, 2026

Oak Ridge, Tennessee, United States
Full-time · Associate

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Lead AI/ML research to develop predictive models for chemical reactions, integrating experimental spectroscopy and molecular simulations.

Compensation

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors.

Responsibilities

Develop and apply deep learning multimodal AI/ML models
Prepare and organize experimental and computational datasets
Develop Bayesian optimization and active learning methods
Develop and demonstrate an automation pipeline
Maintain reproducible code and workflows

Requirements

Ph.D. in chemical engineering, chemistry, computer science, applied mathematics, physics, or a related field
Nice to have: deep learning
Nice to have: Bayesian optimization
Nice to have: Gaussian process
Nice to have: automated scientific workflows

Skills

Python C C++Scikit-learn Keras TensorFlow PyTorch Bayesian optimization active learning Gaussian process high-performance computing parallel job submission scripts software repository tools

Benefits

Prescription Drug Plan
Dental Plan
Vision Plan
401(k) Retirement Plan
Contributory Pension Plan

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Staff Data Scientist Reinforcement Learning – Offer Intelligence (m/f/d)

SIXT · Posted Nov 10, 2026

Lisbon, Lisbon District, Portugal
Hybrid
Staff
5+ years

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Lead the design, development, and deployment of advanced Bayesian and reinforcement learning models to power pricing and offer personalization at SIXT.

Responsibilities

Architect and prototype advanced regression models with Bayesian approach
Design and productionise personalisation and recommendation systems
Apply SVI, MCMC, importance sampling for robust decision-making
Build reproducible pipelines for feature engineering and automated validation
Deploy models via FastAPI, Docker, or Kubeflow and monitor real-time performance

Requirements

Nice to have: Recommender systems
Nice to have: Two-tower retrieval
Nice to have: Embedding-based candidate generation
Nice to have: Learning-to-rank
Nice to have: Sequential models

Skills

Bayesian statistics Hierarchical models State-space methods SVI MCMC Importance sampling

Gaussian Process

Testing frameworks

TensorFlow Probability

Benefits

28 vacation days per year
Additional birthday day off
Volunteer day annually
Private health insurance
Coverflex allowance

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