1 to 25 of 41 Neural Network Jobs in England

We are looking for a goal oriented and driven AI/ML Engineers with relevant experiences. Key Responsibilities: Neural Network Training : Develop and train advanced neural network models to meet specific functional requirements. Deployment and Integration : Efficiently deploy these neural networks on … trends. Skills and Qualifications: Minimum 2 years of experience in building AI/ML software. Strong expertise in machine learning and neural network algorithms. Proficient in programming languages like Python, and frameworks such as TensorFlow or PyTorch. Experience with server deployment, cloud computing environments, and API development. more »

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 »

client delivers systems that can perceive and understand the world with the same semantic richness as the human brain and using the same neural mechanisms they believe are at work in the brain. Their approaches are inspired by their recent advances in theoretical neuroscience, which are beginning to … how the brain makes sense of the world. The project team will work on the development of a novel enhanced convolutional neural network based on a proprietary approach already developed by the company. Applied Computer Vision Data Scientist - job responsibilities: Enhance our machine learning software with the …/computer vision algorithms. Apply existing knowledge of Transformers and CNNs, machine vision & image analysis techniques to the development of enhanced neural network systems based on our research outputs. Work to customise and implement our machine learning solutions for use by prestigious and demanding customers. Contribute to more »

to unlock valuable insights. Responsibilities Spearhead projects with cross functional leaders Use models like regression and propensity models, time-series, ensemble methods and neural networks Seek out opportunities to make an impact using the latest ML methods (NLP and Gen AI) Be the go-to authority for data 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 »

cluster computing and containerization Experience working in parallel/scalable languages such as Spark or Dask Experience working with knowledge graphs and graph neural networks Biotech or biopharma experience, ideally within R&D Experience in a startup or scale-up environment Dewpoint Therapeutics is the first company founded 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 »

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 »

selection, PCA, hypothesis testing, time series, queuing theory, survival analysis, clustering, linear programming. Experience with machine learning methods, such as regularization, random forests, neural networks and deep learning. Ability to write algorithms and implement pipelines in Python. Knowledge of Scala, R, is a plus. Experienced in SQL. Familiarity 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 »

with the ability to write algorithms with ease. Good understanding of data science and machine learning fundamentals like regression, classification, tree-based approach, neural networks, and sequence-based models. Experience with advanced machine learning techniques, including LLM and generative AI for generating high-quality metadata and artwork. Proven more »

and industry-leading computing tools to apply and build ML models from the ground up, utilizing new and established techniques and methods like neural networks, reinforcement learning, deep learning, and natural language processing. Remain connected to the broader research community, staying on top of the latest research and 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 »

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 »

The Role: Your day-to-day responsibilities will include: Working on core segmentation, churn, and recommender system-based projects, alongside deep learning and neural networks to support core clients Part of a team of 8 reporting to the Head of Data Science - working closely with a wider Engineering 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 »

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 »

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 »

in a collaborative and entrepreneurial environment with great opportunities for career progression. Responsibilities: Apply the rigorous scientific method and methods such as NLP, neural networks and deep learning to develop sophisticated trading models across multiple asset classes that inform highly profitable trading strategies. Work with an elite group 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 »

management skills, with a proven track record of delivering projects on time and within scope. fundamentals in programming, statistics, mathematics, and ML algorithms (neural networks, tree-based methods, optimizers, super/unsupervised learning, feature engineering, etc.). Strong experience with Python required understanding of the ML/DS 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 »