Translated with DeepL
Switzerland has a strong education system and highly qualified specialists. However, there are already bottlenecks in specialised niche areas. The Technology Outlook 2025 specifically identifies which skills are in demand in four key technology fields and where there is a need for action.
A differentiated picture is emerging in the area of digitalisation. While Switzerland is well positioned in the fundamentals of quantum technologies, there is a lack of graduates in highly specialised areas. For photonic integrated circuits, an example of a promising future technology, the study identifies the lack of qualified personnel as the most critical bottleneck for the Swiss ecosystem.
These circuits use light instead of electrical signals for data transmission. The advantage lies in significantly higher speeds with lower energy consumption. In data centres, they can reduce power consumption by up to 30 percent. They also open up new possibilities in medical technology, for example for high-precision biosensors. The problem lies in the specific skills required. Specialists are needed who can combine optical physics with semiconductor technology and system design. This combination is rarely taught at Swiss universities.
Specifically, in-depth knowledge of network architectures for real-time communication, knowledge of quantum algorithms and their application as well as expertise in the Internet of Things are required. Industry 5.0 in particular requires specialists who not only operate machines, but also actively participate in their further development.
The approach deliberately places people at the centre. Employees no longer just monitor automated processes, but intervene when necessary, make decisions and optimise processes together with AI systems. A practical example illustrates this. In a production line, an AI recognises an anomaly in the manufacturing process and suggests three possible corrections. The employee evaluates these suggestions based on their experience, selects the most suitable one and gives the AI feedback. The AI learns from the decision and becomes more precise the next time. This form of collaboration requires technical understanding, but also the ability to critically scrutinise and design processes.
For SMEs, this means that the transition to new business models requires corresponding skills within the organisation. The study recommends the targeted promotion of talent and the development of innovation ecosystems.
There is a clear trend in the energy and environment sector: isolated expertise is no longer enough. Carbon capture, hydrogen technologies and deep geothermal energy only work in the overall system. The study explicitly refers to system expertise as a crucial skill.
Specifically, in-depth knowledge of process engineering and chemistry is required, especially for plastics and phosphorus recycling as well as for synthetic fuels. Materials science is becoming increasingly important, as is expertise in plant engineering. Specialists are needed for hydrogen technologies who understand infrastructure, logistics and application across various sectors, from industry to mobility and heat supply.
One example of the required integration can be seen in plastics recycling. It requires not only expertise in process engineering and plant construction, but also an awareness of raw material cycles across the entire value chain. Product developers need to work together with recycling specialists. The study emphasises that it is a question of understanding everything from raw materials, production and the product to services and recycling.
Two areas of expertise are becoming particularly important. Life cycle analysis assesses the environmental impact of a product over its entire life cycle. An engineer developing new packaging must not only test its functionality, but also calculate how much energy is consumed during production, how much CO₂ is emitted during transport, how long the material will remain in use and whether it can be recycled. A concrete example from the food industry illustrates the complexity. A manufacturer wanted to switch from plastic to cardboard in order to be more sustainable. However, the LCA analysis revealed that the cardboard packaging caused more CO₂ during transport due to its higher weight than the lighter plastic packaging, the recycling of which was already established. This holistic assessment is becoming the standard for making products truly sustainable.
At the same time, CO₂ monitoring is becoming mandatory: companies must not only measure their emissions, but also document and reduce them. This requires specialists who are proficient in measurement technology, can analyse data and derive improvement measures. For example, a mechanical engineering company must record the emissions generated when purchasing steel, how much energy its own production consumes, what CO₂ emissions are generated during transport to the customer and what happens at the end of the product life cycle. This data must be validated and reported. In Switzerland, there is still a lack of sufficiently trained people who can take on these tasks.
In manufacturing processes and new materials, traditional disciplines are merging with digital methods. The development of bioplastics from waste, for example, requires an understanding of chemistry, knowledge of polymer and materials science and skills in microbiology. At the same time, knowledge of process and system modelling in combination with artificial intelligence is becoming increasingly important.
For 2D materials, specialists must be able to combine microelectronics and energy generation. When developing flexible batteries, it is important to combine material properties with flexible construction methods. The study concludes that many technologies require a link between material development and application areas.
Switzerland has a strong starting position here with its research expertise and highly qualified specialists. Swiss research groups and start-ups are leaders in niche markets such as the development of synthetic perovskite crystals. However, the availability of skilled labour often does not extend to management levels. If the technologies develop as expected, skilled labour will become a limiting factor.
A profound change is taking place in the life sciences sector. Digitalisation and natural sciences are merging. This can be seen in the working principle of "design, build, test, learn", which is already standard in synthetic biology. With AI, this iterative approach is becoming even more important.
In biocatalysis, the process works like this. Researchers design an enzyme on the computer to catalyse a specific chemical reaction. AI systems suggest variants that could be particularly efficient. In the next step, this enzyme is produced biochemically and its catalytic properties are tested. The results are fed back into the system. The AI learns which structures work and which do not, and suggests optimised variants. This cycle is repeated until the enzyme fulfils the desired industrial requirements.
A Swiss biotech company uses this approach to develop enzymes for the detergent industry. It used to take two to three years before a new enzyme was ready for the market. With AI-supported design and test cycles, this time is reduced to six to nine months. Specialists need to have biochemical expertise, data analysis skills and an understanding of AI methods in equal measure.
In the case of personalised nutrition, specialists must be able to evaluate genetic, biochemical and clinical data. The study predicts that skills in dealing with AI applications and digital twins will become crucial. Data analysis, handling big data and digital twins will also be part of the standard repertoire for SMEs in the life sciences sector in the future.
The study makes it clear that companies in the life sciences must have basic knowledge of engineering and computer science. This is a shift from the traditional profile, which was primarily based on biological and chemical expertise.
Interdisciplinarity has crystallised as a central requirement across all areas of technology. The study formulates it precisely. A specialist from the life sciences must be open to the way of thinking of engineers, computer scientists and materials scientists and productively combine their approaches and problem-solving skills with their own - and vice versa, of course.
It is expressly not a question of relativising specialist knowledge. In-depth expertise remains the basis for innovation. The ability to engage with and understand the mindset of other disciplines is crucial. Interdisciplinary teams thrive on these skills.
Switzerland trains around 80 graduates in quantum physics every year. Of these, an estimated 15 specialise in quantum algorithms, an area that is central to industrial applications. At the same time, several dozen start-ups are currently emerging in the field of quantum computing and established companies are setting up corresponding departments. The arithmetic doesn't add up.
The situation with photonic integrated circuits is similarly precarious. The study identifies the lack of personnel here as the most critical bottleneck. The problem lies in the specific skills required. Specialists are needed who can combine optical physics with semiconductor technology and system design. This combination is rarely taught at Swiss universities. Although ETH Zurich offers individual modules, there is no complete degree programme.
There is no specialised course in deep geothermal energy in Switzerland. If you want to work in this field, you have to combine geosciences, energy technology and drilling technology on your own. Very few succeed in this. Yet the federal government is planning a massive expansion of geothermal energy by 2050. It remains unclear who will build and operate the plants.
The University of Applied Sciences Northwestern Switzerland launched a CAS in Circular Economy in 2023. Interest exceeded expectations and places were filled within weeks. Similar programmes are currently being developed at the ZHAW and Bern University of Applied Sciences. These courses teach life cycle analysis and life cycle assessment, skills that were considered a niche topic just five years ago. Today, SMEs from the mechanical engineering industry and food producers alike are enquiring.
The regulatory framework is making it difficult to develop skilled labour in certain areas. Bacteriophages, viruses that specifically attack bacteria, are considered a promising alternative to antibiotics in medicine. Phage therapies are authorised and routinely used in Georgia and Belgium. In Switzerland, they have not been authorised by Swissmedic. Treatments are only possible in exceptional cases. As a result, no skilled labour base is developing. Researchers who complete a doctorate in this field often leave the country because they see no prospects for application in Switzerland.
There are not enough of the required skills profiles on the labour market. A biotechnology company looking for a biologist with AI expertise and engineering fundamentals is competing with dozens of similarly positioned companies for a handful of graduates. The maths doesn't add up.
Systematic expansion of existing competences is more successful. A chemist with a doctorate and ten years of experience in catalysis research can be trained in machine learning in a year. The result is not a data scientist, but a chemist who can apply algorithmic methods to his speciality. The decisive advantage lies in the domain expertise. The chemist recognises which questions can be solved algorithmically and which chemical parameters are relevant for a model. A computer scientist without a background in chemistry would have to spend years acquiring this knowledge.
The study documents a structural weakness in the Swiss innovation system. While universities conduct excellent basic research, this knowledge is delayed in reaching industrial application. The reason for this is not a lack of willingness to transfer knowledge, but a lack of translation services. An SME needs answers to specific production questions, not scientific papers. This translation requires people who understand both the research logic and the operational reality.
Individual companies are developing new formats for this. A medtech company in western Switzerland employs a member of staff who works half-time in the company and half-time at the ETH. His role is explicitly to translate current research findings into concrete product developments. A textile company in eastern Switzerland regularly sends its process engineers to universities of applied sciences for visits lasting several weeks. There they learn new recycling methods and at the same time confront the university with practical problems that are often neglected in research.
International competition for highly qualified specialists is intensifying. Swiss salary levels alone are no longer enough of an argument. Young researchers are increasingly evaluating the substance of projects, the opportunity for publication and further training as well as the scientific reputation of the working environment. An SME that works exclusively with a product focus and leaves no room for exploratory research will have difficulties attracting talent from the life sciences or materials research. The best candidates have alternatives, both at universities and in large research-intensive companies.
Network architectures for real-time communication, quantum algorithms, optical physics combined with semiconductor technology, active design of human-machine interactions.
Process engineering and chemistry for recycling processes, material sciences for hydrogen and geothermal energy, life cycle analysis, CO₂ monitoring and verification, systems thinking across sectors.
Chemistry and microbiology for bioplastics, process modelling with AI, integration of sensors in complex systems, life cycle assessment across the entire value chain.
Data analysis and big data processing, dealing with AI applications and digital twins, iterative development cycles according to the "design, build, test, learn" principle, basic knowledge in engineering and computer science.
Interdisciplinary thinking, the ability to collaborate across disciplinary boundaries, adaptability to rapid technological change.
Authors: Stefan Scheidegger and Claudia Schärer
The Technology Outlook 2025 of the Swiss Academy of Engineering Sciences (SATW) analyses the skills requirements in the areas of the digital world, energy and the environment, manufacturing processes and materials, and life sciences. The complete study is available at technology-outlook.satw.ch/en/
