1 to 25 of 26 Neural Network Jobs in London

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree‐based models, neural networks, MLOps practices and model deployment. Data Platforms: relational and NoSQL databases, time‐series stores, cloud data services (AWS Redshift, Azure Synapse, Google BigQuery ...

finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational databases, NoSQL, time‐series, big‐data frameworks, cloud data services (AWS, Azure, GCP). Analytics ...

biological datasets (e.g. genomics, transcriptomics, proteomics) Build pipelines for processing and analysing large-scale biological data Apply deep learning techniques (e.g. transformers, graph neural networks) to biological problems Collaborate with wet-lab teams to translate experimental data into actionable insights Optimise models for performance, scalability, and real-world ...

e.g. GLM, GAMs) and deep learning techniques (e.g. neural networks, transformers, diffusion models, etc.). Comfortable designing and creating neural network architectures, tree-based methods and applying upcoming technologies from scratch. We want you to be the creator of the next generation of AI models ...

scalable. What you’ll do: Lead the development and refinement of novel machine learning architectures and algorithms harnessing our nonlinear dynamics. Building deeper network architectures that maximise efficiency and performance. Design, build and test models both on device and using in-house simulation framework. Collaborate closely with the wider … NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals) Hardware Aware ML/Neuromorphic Computing: FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI Unconventional training algorithms Reservoir computing, self-constrastive learning, forward-forward learning, evolutionary algorithms, equilibrium propagation Physics informed neural networks ...

cross-functional teams to identify challenges and implement innovative solutions tailored to the organization’s needs. Qualifications Strong expertise in Pattern Recognition and Neural Networks Proficiency in Computer Science and Software Development Experience in Natural Language Processing (NLP) techniques and applications Proven problem-solving and critical thinking skills ...

000K, plus early equity+benefits Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers. Lead the research and implimentation of data privacy within the models and establish privacy attack-surface assessment Develop and extend models for specific ...

000K, plus early equity+benefits Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers. Lead the research and implimentation of data privacy within the models and establish privacy attack-surface assessment Develop and extend models for specific ...

000K, plus early equity+benefits Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers. Lead the research and implimentation of data privacy within the models and establish privacy attack-surface assessment Develop and extend models for specific ...

000K, plus early equity+benefits Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers. Lead the research and implimentation of data privacy within the models and establish privacy attack-surface assessment Develop and extend models for specific ...

impactful AI solutions. The engineer will work collaboratively across multidisciplinary teams, providing thought leadership in cutting-edge AI technologies, including deep learning, graph neural networks, generative AI, and retrieval augmented system. Required Skills and Experience: 5+ years of professional experience delivering advanced AI/ML solutions in industry … machine learning solutions for enterprise clients, ensuring scalability, reliability, and real‐world impact. Apply advanced AI techniques—including deep learning, classical ML, graph neural networks, object detection, sensor fusion, vector embeddings, retrieval‐augmented generation (RAG), and generative AI models —to design systems that learn, adapt, and operate autonomously. ...

with 2+ years of relevant industry experience; or Bachelor’s degree with 4+ years of relevant industry experience. Strong expertise in deep learning, neural networks, and generative models (diffusion, GANs, transformers). Hands-on experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow). Advanced programming skills … problem-solving, analytical, and communication skills. Ability to work effectively in multidisciplinary, fast-paced, research-driven teams. Preferred Qualifications Experience with 3D vision, neural rendering, or photorealistic rendering pipelines. Familiarity with rendering engines (e.g., Unreal Engine, Unity) or custom 3D engines. Experience with multimodal and foundation models (e.g. ...