21 Neural Network Jobs in the UK excluding London

Performance Tools Engineer in Cambridge, UK About Neubla As pioneers of innovative neural computing, Neubla is transforming the future of computing by bringing the enormous potential of neural computing to the highest performance in most data-intensive applications. Neubla is made up of people with expertise … CPU. However, in AI accelerator domain, the performance model has often been taken lightly due to the regular computation patterns of neural network models. However neural network models are getting bigger and much more complex every month, and it became almost impossible to estimate more »

with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy). Strong knowledge of machine learning techniques and algorithms (e.g., regression, classification, clustering, neural networks). Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) and proficiency in SQL for data extraction and manipulation. Excellent problem-solving skills more »

testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior team members If more »

Science or Robotics. Relevant publications or talks at industry conferences or in journals. Developed machine learning applications in Python. Experience with compilers for neural networks. Experience developing and fielding autonomous systems. Familiarity with Google Cloud Platform. The Candidate Journey: Multi-Step and Two-Way No-one wants to more »

such as numpy, pandas, and scikit-learn Experience with deep learning frameworks (PyTorch, JAX, Keras, Tensorflow) Strong theoretical understanding of machine learning and neural networks Experience with containerized processes (Docker, Kubernetes) Familiarity with cloud services and distributed computing frameworks (AWS, PySpark, Ray Distributed) Problem-solving aptitude and creative more »

or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience in statistical more »

Proficiency in Python Strong NLP experience – NumPy, Pandas etc. Commercial experience leveraging open-source models, finetuning LLMs & RAG pipelines Expertise in learning algorithms, neural networks and ML frameworks (TensorFlow, PyTorch etc.) MLOps experience Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure more »

features, NumPy, keras, pandas, NLTK, scikit, SpaCy > Machine Learning NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) > Strong IaC experience, using Terraform or CloudFormation > Data Wrangling > Systems: Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector 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 »

batch and real-time prediction scenarios: Use machine learning and statistical modeling techniques such as Reinforcement Learning,Decision Trees, Logistic Regression, Bayesian Analysis, Neural Networks and others to develop and evaluate algorithms to improve product/system performance, quality and accuracy Low level systems debugging, performance measurement & optimization more »

features, NumPy, keras, pandas, NLTK, scikit, SpaCy Machine Learning NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) Data Wrangling Systems: Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer desirable skills: Version more »

whilst supporting our employees. We are currently looking for a researcher in our Computing Research Group, working on exploring how the use Graph Neural Networks for healthcare related applications. We have a strong preference for the development of AI techniques that can be applied in the real … world and that directly contribute to social good. Your role will involve: The development of new state-of-the-art Graph Neural Network techniques to be applied to large scale data coming from healthcare applications Implementation of these techniques into proof-of-concept code and demonstrations that more »

Possess a strong foundational knowledge of AI, ML, and data science principles, including signal/pattern recognition, classification techniques, and deep neural network training. Have practical experience with various Data Science and ML frameworks or tools. Excellent verbal and written communication skills Proficient in using MS Office more »

across the business personalising the customer shopping experience online through past behaviours and predictive modelling building and working with models from scratch, across neural networking, segmentation, regression, propensity to buy/churn/lapse analyse the performance and success of statistical modelling, personalisation and marketing performance overseeing a more »

academic publications Excellent written and verbal communication skills The following skills are optional but desirable: · Experience with Graph based algorithms such as Graph Neural Networks · Working with knowledge graphs and graph databases · Experience in a healthcare related field such as cell simulation, bio-informatics or genomics Achieve together more »

sport, animation tools and techniques. Relevant conference, journal, or other peer-reviewed output. Familiarity with GPU techniques for image processing and implementation of neural networks. Familiarity with C++. more »

ML group in the right direction, to the next latest thing in ML. Do you understand the inner workings of a neural network, as well having the know-how to implement on an AI accelerator? Have you spent at least 2 years building your leadership skills in more »

issue that will benefit National Security and Intelligence clients across the world and is equally impactful for other sectors, allowing private access to Neural Networks and Data sets for knowledge growth. If you are interested in delivering impactful product presentations and able to highlight mission-critical benefits of more »

Architect to join their new NPU development centre in Cambridge. This company is developing never-before-seen technology for next generation neural network accelerators for edge devices and datacenters. They are building their Architecture team, seeking a NPU Architect with to innovate NPU (Neural Processing … code, with strong knowledge of either: Computer architecture (CPU/GPU), dataflow architecture, ISA design OR - AI acceleration, machine learning, dataflow architecture, or Neural Processing Unit (NPU)The successful candidate will earn an excellent salary and really enjoy working within this friendly, fast-paced and hugely innovative team. more »

CUDA/OpenCL Kernel Development and a deep understanding of hardware architecture. Responsibilities: Design and develop high-performance CUDA kernels for neural network inference, training, or other compute-intensive tasks. Optimise existing CUDA kernels to improve performance, reduce latency, and minimise power consumption What we need: Strong more »

systems, motor control systems or engine control systems Experience with advanced control strategies or machine learning approaches (e.g., fuzzy logic, adaptive systems, recursive neural networks, convolutional neural networks) Analytical approach to developing control algorithms Extensive knowledge with a range of digital and analog interfaces including GPIB more »