1 to 25 of 31 Permanent Neural Network Jobs in the UK excluding London

D projects to drive step changes in the Stack’s capabilities longer term. The code frameworks you will work on include neural network execution engines, genetic algorithms and training frameworks. This dynamic role will require you to have a broad interest in and experience in software engineering … working collaboratively with other developers on innovative code bases.Experience of genetic algorithms, low level neural network execution and concepts such as neuroplasticity, recurrent neural networks and reinforcement learning frameworks like OpenAI Gym would be a huge advantage. This role requires specific experience with Python and … discipline Strong experience with a statically typed language, preferably C, C++, or Rust Experience with genetic algorithms or neuroevolution Experience with neural network concepts such as neuroplasticity and recurrent neural networks Experience of reinforcement learning frameworks like OpenAI Gym Experience with software optimisation or high More ❯

databases, including SQL (Oracle, Aurora), and Vector DB. Familiarity with version control systems such as Bitbucket and GitHub. Experience with graph analytics and neural networks. Experience working with engineering teams to operationalize machine learning models. Familiarity with the financial services industry. About the Team J.P. Morgan is a More ❯

Research, design, and implement state-of-the-art generative models (diffusion, auto-regressive, etc.) for high-quality image and video generation. - Optimize deep neural networks for deployment on Neural Processing Units (NPUs), maximizing efficiency and performance. - Collaborate with cross-functional teams, including researchers, engineers, and product … developing and optimizing generative models, particularly diffusion and auto-regressive models, for image and video applications. - Strong track record of optimizing neural network architectures specifically for NPUs or other hardware accelerators. - Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). - Excellent analytical, communication, and collaborative More ❯

Research, design, and implement state-of-the-art generative models (diffusion, auto-regressive, etc.) for high-quality image and video generation. - Optimize deep neural networks for deployment on Neural Processing Units (NPUs), maximizing efficiency and performance. - Collaborate with cross-functional teams, including researchers, engineers, and product … developing and optimizing generative models, particularly diffusion and auto-regressive models, for image and video applications. - Strong track record of optimizing neural network architectures specifically for NPUs or other hardware accelerators. - Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). - Excellent analytical, communication, and collaborative More ❯

strong knowledge of ML algorithms, ranging from classical techniques to deep learning methods. Proven experience in training, fine-tuning, and deploying neural network models using frameworks like PyTorch, with a focus on optimizing performance and scalability for real-world applications. Demonstrated ability to mentor and lead technical More ❯

numerous and complex variables - Essential Experience in applying machine learning solutions for genomics investigations - Essential Requirement: Experience using machine learning applications (e.g. convolutional neural networks, recurrent neural networks) - Essential Experience of working on externally funded projects - Essential Experience with next generation sequencing (RNA-Seq, DNA-Seq … based on integration of multi-omic data (genome, transcriptome, epigenome) and integrate this novel information in the development of tissue/condition specific regulatory network, with the aim of prioritising variants occurring within those regions based on their predicted impact. They will also lead on the analysis, preparation, and … submission of the associated manuscripts. The successful candidate will develop computational pipelines centered on machine learning applications such as convolutional neural network to reproducibly handle multi-omic data (genome, transcriptome . click apply for full job details More ❯

Machine Learning for regression and pattern recognition/discovery problems e.g. Gaussian processes, latent variable methods, support vector machines, probabilistic/statistical models, neural networks, Bayesian inference, random-forests, novelty detection, clustering Deep Learning e.g. Deep reinforcement learning, Monte-Carlo tree search, deep regression/classification, deep embeddings More ❯

Delivering high-quality, specification-compliant code. Utilizing tools like OpenCV, TensorFlow, and other computer vision libraries. Applying knowledge of machine learning algorithms and neural networks to enhance processing techniques. Producing high-quality design documentation that adheres to software standards for regulated industries. Demonstrating proficiency in computer vision, image More ❯

general insurance 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 Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering More ❯

general insurance 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 Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering 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 ❯

Delivering high-quality, specification-compliant code. Utilizing tools like OpenCV, TensorFlow, and other computer vision libraries. Applying knowledge of machine learning algorithms and neural networks to enhance processing techniques. Producing high-quality design documentation that adheres to software standards for regulated industries. Demonstrating proficiency in computer vision, image More ❯

great technical understanding of various machine learning approaches, which would include regression methods, probabilistic pricing models, tree based gradient boosting approaches, information theory, neural networks, transfer learning, etc. While your focus will be primarily on the Valuations and Pricing Team you'll also work alongside your peers in More ❯

general insurance 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 Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering More ❯

one hand, Bayesian learning provides a theoretically sound framework to formalise the estimation of the architecture and the parameters of deep neural network models. On the other hand, deep learning offers new tools in Bayesian modelling, e.g. to learn flexible nonparametric priors or computationally efficient posterior distribution … approximations. State of the Art The field of machine learning has recently been much impacted by deep learning. Deep neural networks are now at the basis of the state-of-the-art in computer vision, natural language processing, to cite just a few. While very effective, these models … uncertainty, and it is one of the cornerstones of modern machine learning. At the same time, the theory at the basis of deep neural networks is not yet very well understood and its grounds must be laid out. Although the interaction between these two learning paradigms is relatively More ❯

roles, supported by tailored mentoring and professional training opportunities. You will be encouraged to actively engage in industry and academic events, expanding your professional network and visibility within the quantum technology community. Our collaborative environment ensures that your contributions are recognised and that your career grows alongside our innovative … in cross-functional teams and handing off algorithms to software development teams. Nice to have experience Experience in machine learning, particularly neural network approaches to optical data analysis. Knowledge of anti-counterfeiting technologies or authentication processes. Benefits We are always listening to our team and evolving the More ❯

Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering More ❯

Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering More ❯

including team or project leadership Proficiency in predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering Strong skills in R, Python, PySpark, SAS, or SQL Proven ability to interpret performance data and make commercial recommendations Experience with More ❯

including team or project leadership Proficiency in predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering Strong skills in R, Python, PySpark, SAS, or SQL Proven ability to interpret performance data and make commercial recommendations Experience with More ❯

developing, evaluating, deploying, and updating data-driven models and analytical solutions for spoken language applications. Develop and apply statistical modeling methods (e.g., deep neural networks), optimizations, and other ML techniques for various spoken language engineering applications. BASIC QUALIFICATIONS PhD, or a Master's degree with experience in CS More ❯

and updating of data-driven models and analytical solutions for spoken language applications - Develop and/or apply statistical modelling methods (e.g. deep neural networks), optimizations, and other ML techniques to different applications in spoken language engineering BASIC QUALIFICATIONS - PhD, or a Master's degree and experience in More ❯

experience applying AI in a commercial or customer-focused environment. Hands-on knowledge in areas such as signal processing, reinforcement learning, neural network training, or multi-agent systems. Familiarity with research publishing processes and participation in academic or industry conferences. Responsibilities Leading research initiatives that explore the More ❯

new and exciting ways. If you’re looking for a challenging career working in a vibrant environment with access to training and a global network of experts, this could be the role for you. As part of our global team, you'll be working with cutting-edge technologies and … Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the More ❯

machine learning Ideally, you will also have: Experience in molecular simulation, cheminformatics or bioinformatics Experience with advanced machine learning methods (generative modelling, graph neural networks) Not sure if you meet the requirements? We recognise that great candidates come from different backgrounds, and we would love to hear from More ❯