Research associate (m/f/x) in Data Science in Chemistry
Core
Postdoctoral researcher applying data science and machine learning to model reaction networks, predict reactivity/selectivity/yield, and identify new catalysts in organometallic synthesis and homogeneous catalysis.
Role type
Postdoctoral researcher (scientific staff)
Builds
Data-driven models of reaction networks and catalyst identification
Domain
Chemistry (Organometallic synthesis, Homogeneous catalysis) + Machine Learning
Deliverable
production ML models | research
Required skills
Quantum-chemical calculations, Machine learning, Python programming, Statistical analysis, Research project management, Scientific publishing, Teaching
Preferred skills
Homogeneous catalysis experience, High-performance computing cluster management
Technologies
ORCA, Multiwfn, AIM, NumPy, SciPy, pandas, Scikit-learn, RDKit, PyTorch
Responsibilities
Perform quantum-chemical calculations to elucidate reaction mechanisms; Create and validate models for structure-activity relationships; Collaborate with experimentalists to validate data collection; Supervise students and support teaching in Data Science/ML; Compile results into publications
Seniority
Postdoctoral researcher
