We might be able to help you. The Siemens Lisbon Tech Hub has more than 700 employees with several IT expertise: Application Development, Artificial Intelligence, Big-Data and Robotics, User Experience, Project Management and much more, making it one of the largest in Europe – check it out: www.siemens.pt/lxtechhub Fresh fruit and coffee, remote work, medical center in the facilities, sport groups, volunteering hours, sushi&pizza days, office parties and games in a cool and relaxed environment. We recognize that building a diverse workforce is essential to the success of our business. Therefore, Siemens provides equal employment opportunities to all qualified individuals without regard to race, creed, color, religion, national origin, age, sex, marital status, sexual preference, or non-disqualifying physical or mental handicap or disability.

In case you have acquired your skills in alternative ways your application is just as well appreciated. What else do I need to know? Siemens is dedicated to equality and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit and business need. Bring your curiosity and imagination and help us shape tomorrow. We are looking forward to receiving your online application. Please ensure you complete all areas of the application form to the best of your ability as we will use the data to review your suitability for the role.

Universal Approximation Theorem says that Feed-Forward Neural Network (also known as Multi-layered Network of Neurons) can act as powerful approximation to learn the non-linear relationship between the input and output. But the problem with the Feed-Forward Neural Network is that the network is prone to over-fitting due to the presence of many parameters within the network to learn. Can we have another type of neural network that can learn complex non-linear relationship but with fewer parameters and hence prone to over-fitting?. Convolution Neural Network (CNN) is another type of neural network that can be used to enable machines to visualize things and perform tasks such as image classification, image recognition, object detection, instance segmentation etc…are some of the most common areas where CNN's are used. In this article, we will explore the workings of the Convolution Neural Network in-depth.

Based on Apache OpenWhisk, IBM Cloud Functions is a Functions as a Service (FaaS) platform that makes it easy to build and deploy serverless applications. In this tutorial, you'll build a serverless application using IBM Cloud Functions that monitors the content of a Cloud Object Storage bucket and analyzes the content of images that are uploaded to the bucket by a human or an automated process. For illustrative purposes, analysis is performed by a deep learning microservice from the Model Asset eXchange and analysis results are stored as JSON files in the same bucket. You can easily adapt the outlined approach to take advantage of hosted cognitive services, such as those provided by IBM Watson, and to store results in a NoSQL datastore like Cloudant or a relational database. By completing this introductory tutorial, you learn how to monitor a Cloud Object Storage bucket for changes (new objects, updated objects, or deleted objects) using Cloud Functions and how to use deep learning microservices from the Model Asset eXchange to automatically analyze those objects in near real time.

In August 2019 the UK government announced a welcome boost for artificial intelligence (AI) in health care, with £250m for a national laboratory in England. Public imagination is captivated by robots, but the new lab will prioritise technologies more likely to benefit the health system and patients in the short term, including algorithms to predict demand for hospital beds and tools that identify signs of disease from diagnostic images, all underpinned by a focus on ethical and fair AI. Many health care professionals rely on paper records and outdated technology, and struggle to access basic information at the point of care. Investment is needed, but this must be matched with a credible national strategy for AI and data analytics that focuses on the needs of patients and the health system rather than technology for technology's sake. The priorities of NHSX, the national agency for digital transformation in health care that will host the AI lab, include reducing clinicians' workloads, giving patients tools to access services directly, ensuring clinical information can be accessed safely where needed, enhancing patient safety, and improving productivity.

Identity fraud, in which a slice of your identity ranging from new credit cards to entire bank accounts is taken over by criminals, rose by 49 per cent in 2015 on the previous year. That totalled almost 170,000 cases, according to data collected by Cifas, the financial industry's non-profit fraud advisory service. The reason for the rise is that more and more we use the internet for financial transactions, but have very few ways to verify our identity without cumbersome systems involving human interaction, which are also vulnerable to fraud. Cifas' 2015 Fraudscape report shows that 86 per cent of identity fraud happened online, with bank accounts and credit or debit cards most targeted, closely followed by loans and communications, typically mobile phone accounts. Businesses looking to tackle fraud are turning to artificial intelligence and deploying neural networks because the systems learn in a manner like the brain's own neurons to try to bust fraud Traditionally, companies dealing with such problems have acted after the fact, trying to unravel complex or opportunistic frauds by working back through audit trails.

Alphabet is disrupting healthcare, auto, government contracts, and more with AI. We look at how it got here, where it's headed, and what this means for incumbents. Google was relentless in its pursuit of artificial intelligence even before the current wave of AI commercialization took off. It may be hard to imagine a time when neural networks -- AI algorithms initially inspired by biological neural networks -- were having a dry spell. But researchers were bearish on its commercial scalability as recently as the early 2000s.

Washington, Oct 25 (ANI): Do you also face trouble while selecting clothes and seeking fashion advice? Seems like your phone will be your helping hand soon. A University of Texas at Austin computer science team, in partnership with researchers from Cornell Tech, Georgia Tech, and Facebook AI Research, has developed an artificial intelligence system that can look at a photo of an outfit and suggest helpful tips to make it more fashionable. Suggestions may include tweaks such as selecting a sleeveless top or a longer jacket. "We thought of it like a friend giving you feedback," said Kristen Grauman, a professor of computer science whose previous research has largely focused on visual recognition for artificial intelligence.

Pinterest announced on World Mental Health Day that it's reduced self-harm content by 88 percent over the past year using AI. In a blog post titled Getting better at helping people feel better, the social media platform says it's using machine learning techniques to identify content which displays, encourages, or rationalises self-harm. Anxiety and depression are at all-time highs while many countries are failing to properly fund mental health services. In the UK, someone commits suicide every 90 minutes. Experts believe social media plays a large part in the record levels of anxiety and depression.

The US government has awarded a giant $10 billion cloud contract to Microsoft, the Department of Defense has confirmed. Known as Joint Enterprise Defense Infrastructure (JEDI), the contract will provide the Pentagon with cloud services for basic storage and power all the way up to artificial intelligence processing, machine learning, and the ability to process mission-critical workloads. It's a key contract for Microsoft as the company battles Amazon for cloud dominance, and for a while it was up in the air as to whether Microsoft or Amazon would win this particular one. IBM and Oracle were both eliminated for the bidding back in April, leaving just Microsoft and Amazon as the only companies that could meet the requirements. The contract has been controversial throughout the bidding process, and Oracle lost a legal challenge after it claimed the contract has conflicts of interest.