Looking to embark on a career in the deep-tech industry? From quantum computing to machine learning, there are plenty of exciting roles and skills to explore. Read on to discover what you need to know to excel in this rapidly growing field.
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In recent years, the deep-tech industry has gained significant momentum. Deep tech encompasses innovations based on scientific discoveries and engineering expertise that have the potential to disrupt multiple industries. With the rise of digital transformation, quantum computing, generative AI, and the urgent need for a sustainable future, the demand for a strong deep-tech ecosystem has never been greater.
Oppo A79's Promotional Materials Reveal Its DesignTo meet this demand, more deep-tech startups are emerging, along with the necessary support systems to foster their growth. Additionally, established industry players and giants are actively seeking talent with deep-tech skills. So, what are the most sought-after roles and which skills should you focus on to thrive in this exciting domain?
"The deep-tech industry has experienced significant growth due to continuous investment and research," explains Ian Storey, a director in Hays Technology. "Universities, research institutions, and companies are investing in new scientific concepts, leading to accelerated breakthroughs and constant innovation."
Calvin Lan assumes the role of CEO at Huawei IrelandOne reason for this growth is the increasing access to data and advancements in data analytics and machine learning. Collaboration between scientists and entrepreneurs has also flourished as the demand for innovative solutions to real-world challenges continues to rise.
"Businesses and investors are showing a growing interest in deep tech," says Storey. "Deep-tech ventures have a profound impact, tackling large-scale issues while simultaneously pushing the boundaries of what's possible."
TECNO Celebrates Distinguished Multi-Skin Tone Imaging Technology with 'Portrait for Everyone' Short FilmExplore the Most In-Demand Roles in Deep Tech:
- Data scientist
- Machine learning engineer
- AI research scientist
- Bioinformatics specialist
- Blockchain developer
- Quantum computing scientist
- Robotics engineer
- Augmented reality developer
Data scientists have consistently been in high demand within the tech industry due to the critical value of data in today's evolving technological landscape. Unsurprisingly, the need for machine learning engineers and AI research scientists has skyrocketed alongside increased investment in AI. Bioinformatics, an interdisciplinary field merging biology and computer science, has also become increasingly valuable in life sciences and health research. Furthermore, blockchain expertise is highly sought after in fintech, security, and Web3. As advancements in the fields of quantum computing, robotics, and augmented reality continue, the demand for skilled engineers and scientists in these areas will only grow stronger.
Key Skills for a Career in Deep Tech:
To thrive in the deep-tech industry, it's crucial to possess the right skills. Storey emphasizes the importance of proven industry experience in implementing machine learning and deep learning solutions. He highlights the need for expertise in deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative models. Proficiency in programming languages like Python or C++ and experience with machine learning frameworks such as TensorFlow or PyTorch are also advantageous.
Samsung Galaxy S23 series receives ninth One UI 6 beta releaseAdditionally, problem-solving skills are essential in this field, as professionals must be able to apply their technical expertise to real-world challenges. Storey recommends focusing on training in related technologies like Python or C++ to gain a foothold in the industry. Working for organizations that invest in deep learning and already have a deep learning strategy can provide valuable exposure, even if the role itself isn't purely focused on deep learning.
From an educational standpoint, pursuing a master's degree or PhD in machine learning or a related field is worth considering to further enhance your qualifications in the deep-tech domain.
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