15 of 15 Convolutional Neural Network Jobs in England

problems with 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 … 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 ❯

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 centred on machine learning applications such as convolutional neural network to reproducibly handle multi-omic data (genome, transcriptome, epigenome) to enable functional sequence annotation, network reconstruction, and the interpretation of the implication of genetic More ❯

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 centred on machine learning applications such as convolutional neural network to reproducibly handle multi-omic data (genome, transcriptome, epigenome) to enable functional sequence annotation, network reconstruction, and the interpretation of the implication of genetic More ❯

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 centred on machine learning applications such as convolutional neural network to reproducibly handle multi-omic data (genome, transcriptome, epigenome) to enable functional sequence annotation, network reconstruction, and the interpretation of the implication of genetic More ❯

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 centred on machine learning applications such as convolutional neural network to reproducibly handle multi-omic data (genome, transcriptome, epigenome) to enable functional sequence annotation, network reconstruction, and the interpretation of the implication of genetic More ❯

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 centred on machine learning applications such as convolutional neural network to reproducibly handle multi-omic data (genome, transcriptome, epigenome) to enable functional sequence annotation, network reconstruction, and the interpretation of the implication of genetic More ❯

with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance. Hands-on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer). Prior experience in training and fine-tuning of Large Language Models (LLMs) and knowledge of AWS platform and tools or equivalent More ❯

machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience. Hands-on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer). Prior experience in training and fine-tuning of Large Language Models (LLMs) and knowledge of AWS platform and tools. Amazon is More ❯

or computer science. 5+ years of machine learning/statistical modeling data analysis tools and techniques experience. Hands-on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer). Prior experience in training and fine-tuning of Large Language Models (LLMs) and knowledge of AWS platform and tools. Amazon is More ❯

with AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2. Hands-on experience with deep learning techniques (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training. Excellent communication skills, with the ability to explain complex mathematical concepts to non-experts. Amazon More ❯

in at least one of Python, Rust, or C++ with Linux operating system experience and experience fine-tuning models (e.g., RNN, LSTM, BERT, LLM, CNN) and deploying them to production. You will also ideally have: Strong knowledge of more than one programming language, Experience developing software for Windows or MacOS More ❯

transform video on the desktop and across the enterprise. Many of the world's most demanding media and entertainment companies such as CBS, BBC, CNN, FOX, CBC, Comcast, Direct TV, Time Warner, MTV, Discovery and Lifetime, as well as a growing number of users in a broad range of business More ❯

an advocate for engineering best practices.WBD'sGlobal Content Delivery team members are responsible for the management & governance all media delivery infrastructure for Max, D+, CNN, and other WBD brands globally. You will be involved from the initial design phase of figuring out the right network topology for our clients … new revisions of hardware to deployed to the field. This team works the full stack from software, networking, operating system, to the hardware and network gear level. Design, write and deliver software and infrastructure to improve the reliability, scalability, latency, and efficiency of our services. Bring new technology thinking … environment. Collaborate with the Platform Engineering team to build tools to help automate deployments. Coordinate with relevant teams to build useful tools to support network operations (internal and external). Qualifications and Experience The Essentials: Passionate about SRE, DevOps, Automation, and infrastructure platforms. Understand the mechanical sympathy between software More ❯

most prestigious Fortune 500 companies such as Samsung, Coca Cola, Nike, L'Oreal, Singapore Airlines, Virgin, Nestle, Nissan, Lenovo, Puma, IKEA, Allianz, Dominos, Avon, CNN, and the list goes on. Having recently unlocked unicorn status, Insider was congratulated for becoming one of the only woman-founded, women-led B2B SaaS … covering for your private medical care. a chance to work in an international, diverse, and inclusive environment, access and opportunity to gain a limitless network all over the globe, a chance to become a Shareowner with the "Shareowner System" that we offer to all Insiders who meet certain criteria More ❯

Welcome to Warner Bros. Discovery the stuff dreams are made of. Who We Are When we say, "the stuff dreams are made of," we're not just referring to the world of wizards, dragons and superheroes, or even to the More ❯