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Assistant Professors Artificial Intelligence (Tenure Track) 1,0 fte

We offer a tenure track position (0.8 - 1.0 FTE) for five years in an international working environment. Successful candidates receive a tenure track position, which is turned into a permanent position when our tenure requirements are met (these are available upon request).

The gross salary - depending on previous qualifications and experience  - ranges between  € 3,637 and € 5,656 (scale 11-12 according to the Collective Labour Agreement Dutch Universities) per month for a full-time employment).

Data Science vs. Machine Learning vs. Artificial Intelligence

As the global business environment is fast moving toward “all things digital,” as predicted by Gartner a while back, artificial intelligence (AI), machine learning (ML), and deep learning (DL) will play as important roles as Data Science in reshaping businesses across the world.

The author also mentions that it is critical for businesses to understand the sharp difference between Data Management and Data Strategy, because the latter facilitates the former through a carefully guided framework of plans, programs, policies, and practices.

These favorite buzz words often trending on technology news sites combine principles of mathematics, statistics, computer science, data engineering, database technologies, and more.

Data Science may be viewed more as the technology field of data management that uses AI and allied fields to interpret historical data, recognize patterns in current data, and make future predictions.

The overnight transformation of business processes and day-to-day decision-making, further fueled by Big Data, Hadoop, and the rise of social, mobile, and IoT channels, brought data technologies to the forefront of business operations.

“Data Science” is the more holistic term encompassing the “collection, storage, organization, preparation, and end-to-end management of data,” while the AI-enabled technologies control and facilitate data analytics in business operations.

Though Data Science itself is an inter-disciplinary field, when data scientists enter the realm of data analysis, they begin at the top automation level of AI, working their way down to DL with increasingly more complex and more challenging analysis tasks.

The neural networks function like the human brain, and intense analytics activities require a “brain-simulator kind of environment” to resolve highly complex business problems.

The post states that while the ML expert remains pre-occupied with building useful algorithms throughout the project lifecycle, the data scientist has to be a little more flexible in role-playing — switching between different data roles according to the needs of the project.

It points out that while AI and ML provide answers to business problems, the data scientist finally comes to build a convincing story through visualization and reporting tools for the consumption of a broader business audience.

The business audience may not understand what a random forest is, but once the data-driven story is in front of them, they immediately understand the relationships and patterns among different business components, along with their future impact on business.

AI and ML work together to automate human activities like customer service (digital assistants), driving vehicles (self-driving cars), and offering personalized recommendations (recommendation engines).

Deep Learning, the author points out that in ML, the training algorithms learn from a single layer, while in DL, the same training of algorithms happens in multiple layers, in what is known as “unsupervised learning.” The learning in DL closely simulates human learning conditions.

Lecturer/Senior Lecturer in Computer Science, Artificial Intelligence

To be confirmed The University is seeking to recruit a Lecturer or Senior Lecturer in Computer Science, who wishes to embark on an academic career conducting quality research and lecturing on postgraduate and undergraduate programmes.

The successful candidate will work closely with departmental academic teams and be expected to contribute to existing teaching and research.

The role has a strong emphasis on, and support for, research and enterprise activity, including participation in projects jointly launched by other members of the Department and Faculty.

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