1 to 14 of 14 Neural Network Jobs in England with Remote Work Options

discipline e.g. engineering, mathematics, physics, statistics Experience of data science in finance, insurance or Ecommerce is an advantage but not required. Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas Our technology We are currently developing a new data platform in databricks that encompasses all our more »

Engineer Strong foundation in Python Excellent knowledge of ML libraries and frameworks like TensorFlow, PyTorch, Keras and scikit-learn. Experience with neural network architectures, deep learning techniques, and building and training deep learning models. Creating and handling large datasets including pre-processing steps and familiarity with data more »

to join a new and growing company working on Analog AI accelerator projects which utilizes Analog processing-in-memory to expedite neural network workloads. In this role you will be responsible for hands on Analog IC Design in the initial stage whilst building up a team of more »

The Company Luffy AI is an exciting high-tech startup developing adaptive neural networks for industrial control. Luffy specialises in adaptive neural networks that can be trained in simulation on digital twins and successfully transferred into real world systems. Our networks use neural plasticity more »

and various foundational LLM's for Retrieval Augmented Generation (RAG) architecture including opensource would be desirable. Experience with graph machine learning (i.e., graph neural networks, graph data science) and practical applications thereof. This is complimented by your experience working with Knowledge Graph, creating ontologies leveraging Neo4j, GraphDB and more »

well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture. Expertise in graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof. This is complimented by your experience working with Knowledge Graphs, ideally biological, and a familiarity with more »

advanced analytics or machine learning algorithms. An understanding of data science and machine learning concepts and algorithms such as clustering, regression, classification, forecasting, neural networks, hyperparameter tuning, NLP, and utilising LLMs. An understanding of the importance of effective communication with clients and experience of relaying complex technical concepts more »

to solve real world financial problems Build/run in-house developed and third party ML models in production Deep learning research (Graph Neural Networks) Natural language processing (Semantic search, Generative LLMs) Datapoint extraction Develop novel methods to facilitate financial research from unstructured data. We are a research more »

Autonomous Driving product. We are looking for an experienced Machine Learning Engineer to help us in our journey to scale end-to-end neural networks for autonomous driving. You ll be working across our embodied AI org team to build, integrate, test and scale algorithms, tools, and machine more »

of these areas). You will look at the latest development within ML and design and deliver these across ML and Neural Network Methodologies. You will be involved in data analysis and statistical modelling. You will be writing high quality code and deploying these models both on more »

benefit of the team. QUALIFICATIONS A postgraduate degree in Computer Science, Machine Learning, or a related scientific field. Proven experience in deep learning, neural networks, and the development of AI models. Strong expertise in language models, particularly in transformersProficiency in programming languages such as Python, along with familiarity … Qualifications: Language requirements: Specific requirements: Educational level: Level of experience (years): Senior (5+ years of experience) Tagged as: Academia , Language Modeling , Machine Learning , Neural Networks , NLP , United Kingdom #J-18808-Ljbffr more »

Strong Python skills and understanding of data science and machine learning concepts and algorithms such as clustering, regression, classification, forecasting/predictive analytics, neural networks, hyperparameter tuning, NLP, and utilising LLMs. - **Communication:** Strong ability to communicate complex technical concepts to diverse audiences effectively. - **Management:** Previous line management experience. more »

with numerous publications at prestigious conferences. As a Research Engineer, you'll collaborate globally to tackle complex deep learning challenges, focusing on graph neural networks and pioneering new foundation models in healthcare. The Impact Your research will directly contribute to real-world applications with a profound social impact more »

knowledge graphs (KG) by reasoning over and inferencing from existing KG data using graph data science (GDS), graph machine learning (GML), and Graph Neural Networks (GNNs) approaches. Benefits and Perks: An engaging remote-first culture A great compensation package that includes BenchSci equity options A robust vacation policy more »