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Machine learning scientist
- London, England, United Kingdom
- London, England, United Kingdom
Über
machine learning to molecular systems , e.g. protein engineering, enzyme catalysis, reaction prediction, molecular
de novo
design, molecular dynamics. Strong background working with
deep learning architectures
relevant to molecules/sequences: -Transformers (e.g. ProtBERT, ESM, AlphaFold-like) -Generative models (diffusion, VAEs, autoregressive) for proteins, molecules or materials. Hands-on experience with
molecular dynamics and simulation data ; familiarity with force fields, ab initio methods, or enhanced sampling. Strong programming in Python (PyTorch/TensorFlow, JAX, NumPy/SciPy); experience with scientific libraries such as RDKit, ASE, DeepChem. Experience with
MLOps
and end-to-end large-scale model development. (e.g. training, evaluation, benchmarking and deployment) Familiarity with vector databases and embeddings (Qdrant, Milvus, FAISS) for chemical/sequence similarity search. HPC/GPU cluster experience, performance optimisation, distributed training. Background in spectroscopy (IR/UV/Vis/NMR) and/or computational thermodynamics/kinetics. Exposure to enzyme engineering, biocatalysis, or structural biology data. What we offer Opportunity to build a machine learning stack from the ground up, with direct impact on real-world sustainable chemistry. A highly collaborative lab–computational environment: every model prediction is tested in-house, feeding back into data pipelines. Central London lab/office with a fast-growing interdisciplinary team. Seniority level: Mid-Senior level Employment type: Full-time
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Sprachkenntnisse
- English
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