For a quick glance at whether you meet this criterion individually, the Schengen countries are as follows:. As previously stated, acquiring a work permit in Iceland is a difficult process; legislation exists that prioritises both Icelanders and EEA citizens above their international counterparts an exception to this is those coming to the country with a specialised skill.
Requires vocational training to University level, or to an approved technical standard. Athletes and coaches belonging to National Olympic teams or a club under the Sporting Association of Iceland may also be granted visas. Temporary Shortage of Labourers: Whichever field is currently lacking in Icelandic or EEA employment can open up the possibility of temporary work permits, though these can only be renewed once.
When preparing for a job hunt, the first thing to do is to sit back and consider your skills, experience and passions. What type of employment would best suit you? What type of positions have you held in the past? Are you looking for a new career direction, or simply hoping to work part-time? What type of role is most abundant in Iceland? Questions such as these are important to clarify, shedding light on the next steps of the job hunting process and thus, simplifying your means to an application.
Applications should be sent by email with a small introductory message and your application documents attached. If after a few days there has been no confirmation that the application has been received, it is more than acceptable to send a follow-up email or phone call. This means that it is imperative that your CV and cover letter stands out from the crowd; after all, it takes only a few seconds for someone to get the wrong impression and hastily dismiss an application altogether.
Because of this apparent danger, CV and cover letter writing should be incredibly succinct. No prospective employer wants to read pages upon pages of your high school achievements, nor will they trust an applicant who is unable to get across their best features concisely. In Iceland, a one page CV and a one-page cover letter is the expected length.
It is also wise to consider the individual qualities that an employer is looking for in a job applicant and to make sure that such characteristics are conveyed concisely in your application. A quick search on google will reveal these attributes to be; honesty, communication skills, flexibility, determination, a willingness to learn and engage and to work in harmony with other team members.
By using a referee , it shows the prospective employer that you are confident in yourself and what you have previously achieved and also demonstrates that you have nothing to hide, but in fact are willing to have another vouch for your work ethic. Of course, it goes without saying that you must feel self-assured that your referee will provide positive feedback otherwise, you can guarantee the Achilles heel of your application has been found.
Alternatively, you could use a letter of reference that has already been provided to you. This way, you can be certain of the information being put across in your application. In Iceland, interviews are regularly taken in person, though those applying from abroad will likely use the telephone or Skype. Quite often, job interviews will take a more informal approach in Iceland—i. Iceland is a small community, so employers want to make sure that they're hiring someone who is not only qualified for the position but is also a pleasure to have around the office.
Wherever they occur across the world, a job interview is a job interview, a formal consultation where one individual will assess the qualities and character of another through a series of insightful questions. As with any modern European nation, the range of employment sectors across Iceland is staggering. A prospective employee has any number of different job sectors in which to explore and apply; finance, business management, creative arts and design, energy and utilities, engineering, law, the media, etc.
With such a wealth of options, applicants will most often keep their doors open, applying for a range of positions that suit their qualities. After all, the more applications out there, the more likely an interview opportunity is to arrive—sometimes, a less desirable position is necessary until a more fulfilling opening becomes available. The largest sectors, by far, are manufacturing, fishing and tourism, all three of which are vital contributors to the Icelandic economy.
Aluminium smelting is an energy-intensive process; smelters extract aluminium from its oxide, alumina, using copious amounts of electricity and producing a high level of fluoride waste. Iceland is 11th place amongst aluminium-producing nations globally. It is also just as easy to picture the bigwigs at Rio Tinto Alcan, Century Aluminum Company and Alcoa all rubbing their hands wolfishly at the prospect of such plentiful and cheap power, all without much consideration for the impact such industry brings to a natural ecosystem.
Unsurprisingly, resistance at home has been fierce, with great swathes of the population unified under the banner environmental protection. As with almost all island populations, Icelanders have long maintained a strong connection to the sea. The harsh, Atlantic waters have, in many ways, defined the country entirely, sculpting its weather patterns, its cragged shoreline, its vexing isolation.
So too has it shaped the identity of Icelanders, a seafaring people who are quick to brave the ocean for its bounty and promise. With nautical square miles of fertile fishing grounds, Iceland has managed to create one of the most modern and sustainable seafood industries on the planet. In the s and s, Iceland and the United Kingdom became caught up in a series of territorial disputes regarding who had rights over certain fishing grounds. Iceland had extended its fishing borders into what was perceived to be international waters, a trend that coincided with the invention of the mechanised fishing trawler, a ship that could travel much further from the mainland.
The United Kingdom took this as a threat to their own fishing industry and quickly retaliated by sending military vessels to intercept and disrupt the Icelandic trawlers. These disputes have since become known as "The Cod Wars" and were only resolved in after the Icelandic government threatened to close down the NATO base at Keflavik. Thankfully, no one died during these disputes, though there were a great number of deliberate collisions that occurred between British and Icelandic ships.
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Blue Lagoon Shuttle Bus Transfer. It also means that tourism is set to be on the biggest employment sectors in Iceland, hiring, amongst others: Over the last decade, tourism has worked itself into the fabric of almost every corner of life in Iceland; downtown is often jam-packed with international visitors, tour companies are forever growing in prominence, and new shops, restaurants and exhibitions are always arising to meet the growing needs of tourists. But why did this all begin? Well, Iceland first made international attention in following the country's rapid financial collapse.
Suddenly, this once overlooked island in the Mid-Atlantic was now fixed in the gaze of international travellers. Collectively, the Icelandic government, its tourist board and travel agencies came together to turn what could have been their downfall into a swift economic victory. Even the engineers who build these apps cannot fully explain their behavior.
This raises mind-boggling questions. As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Will that also be possible with machines that think and make decisions differently from the way a human would? How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable? These questions took me on a journey to the bleeding edge of research on AI algorithms, from Google to Apple and many places in between, including a meeting with one of the great philosophers of our time.
This data set features hundreds of variables on patients, drawn from their test results, doctor visits, and so on. The resulting program, which the researchers named Deep Patient, was trained using data from about , individuals, and when tested on new records, it proved incredibly good at predicting disease.
Without any expert instruction, Deep Patient had discovered patterns hidden in the hospital data that seemed to indicate when people were on the way to a wide range of ailments, including cancer of the liver. At the same time, Deep Patient is a bit puzzling.
It appears to anticipate the onset of psychiatric disorders like schizophrenia surprisingly well. But since schizophrenia is notoriously difficult for physicians to predict, Dudley wondered how this was possible. The new tool offers no clue as to how it does this. If something like Deep Patient is actually going to help doctors, it will ideally give them the rationale for its prediction, to reassure them that it is accurate and to justify, say, a change in the drugs someone is being prescribed. From the outset, there were two schools of thought regarding how understandable, or explainable, AI ought to be.
Many thought it made the most sense to build machines that reasoned according to rules and logic, making their inner workings transparent to anyone who cared to examine some code. Others felt that intelligence would more easily emerge if machines took inspiration from biology, and learned by observing and experiencing. This meant turning computer programming on its head.
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Instead of a programmer writing the commands to solve a problem, the program generates its own algorithm based on example data and a desired output. Then the computerization of many industries and the emergence of large data sets renewed interest. That inspired the development of more powerful machine-learning techniques, especially new versions of one known as the artificial neural network.
By the s, neural networks could automatically digitize handwritten characters. It has given computers extraordinary powers, like the ability to recognize spoken words almost as well as a person could, a skill too complex to code into the machine by hand. Deep learning has transformed computer vision and dramatically improved machine translation. It is now being used to guide all sorts of key decisions in medicine, finance, manufacturing—and beyond.
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The workings of any machine-learning technology are inherently more opaque, even to computer scientists, than a hand-coded system. This is not to say that all future AI techniques will be equally unknowable. But by its nature, deep learning is a particularly dark black box. The neurons in the first layer each receive an input, like the intensity of a pixel in an image, and then perform a calculation before outputting a new signal. These outputs are fed, in a complex web, to the neurons in the next layer, and so on, until an overall output is produced.
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Plus, there is a process known as back-propagation that tweaks the calculations of individual neurons in a way that lets the network learn to produce a desired output. The many layers in a deep network enable it to recognize things at different levels of abstraction. In a system designed to recognize dogs, for instance, the lower layers recognize simple things like outlines or color; higher layers recognize more complex stuff like fur or eyes; and the topmost layer identifies it all as a dog.
The same approach can be applied, roughly speaking, to other inputs that lead a machine to teach itself: In , researchers at Google modified a deep-learning-based image recognition algorithm so that instead of spotting objects in photos, it would generate or modify them. By effectively running the algorithm in reverse, they could discover the features the program uses to recognize, say, a bird or building.
The resulting images , produced by a project known as Deep Dream, showed grotesque, alien-like animals emerging from clouds and plants, and hallucinatory pagodas blooming across forests and mountain ranges.
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But the images also hinted at how different deep learning is from human perception, in that it might make something out of an artifact that we would know to ignore. Google researchers noted that when its algorithm generated images of a dumbbell, it also generated a human arm holding it. Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers.
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