Tandem Industry Academia (TIA) Postdoc (2024)
Breaking bottlenecks in drug development has potential to revolutionize industry
Project title:
Surface functionalized core/shell drug crystal nanoparticle platform for targeted delivery
Approved funding:
195 005 €
Applicant:
Åbo Akademi
Industrial partner:
Bayer
“I have been collaborating with Bayer for a few years now, and we have common research interests that we’d like to explore further. That’s why we applied for this grant, and we’re delighted to get the funding.”
Hongbo Zhang, Principal investigator
Many new drugs show great promise in laboratory trials, but they often have poor solubility or fail to reach their targeted site. This joint project between Åbo Akademi and Bayer uses microfluidics technology to develop surface-functionalized, nanosized drug crystals for more accurate and targeted drug delivery. Improved drug solubility and targeting contributes to improved drug efficacy and safety. The collaborative setting will facilitate the transfer of academic discoveries directly into commercial product development. In this way the project could have momentous impact on pharmaceuticals development globally.
New measuring device to reduce ruminant greenhouse gas emissions
Project title:
Developing optimal methane mitigation strategy for milk production by animal breeding
Approved funding:
275 059 €
Applicant:
Natural Resources Institute Finland
Industrial partner:
Valio
“Research collaboration with a corporate partner enables the rapid practical application of research results.”
Pekka Huhtanen, Principal investigator
Methane emissions from ruminants are a key factor in reducing the environmental footprint of dairy production. Methane levels can be reduced either by selecting low-emitting cows or indirectly by improving feed efficiency. The assessment of feed efficiency, however, has been complicated by the absence of technically and economically feasible tools. This joint project between Natural Resources Institute Finland and Valio will be working to develop a method for detailed analysis of feed efficiency based on the measurement of cows’ respiratory gases. The volume of oxygen consumed and carbon dioxide produced provide crucial information on the metabolism of cows. The same device can be used to simultaneously measure the gas exchange of about 25 cows, and the data generated can help to reduce both methane emissions from dairy production and other environmentally detrimental gases.
Life cycle analysis of Finnish road network supports fossil-free and carbon-neutral goals
Project title:
Development of an artificial intelligence integrated full life cycle assessment tool for road infrastructure in Finland – AI-FINROADS
Approved funding:
208 595 €
Applicant:
Aalto University
Industrial partner:
Ramboll Finland
“We envisage that by combining the existing data pool of Ramboll and Aalto University’s expertise in circular road construction, we can develop robust and resilient LCA (Life Cycle Assessment) frameworks for Finland.”
Sanandam Bordoloi, Principal investigator
What is the environmental impact of road transport? Aalto University and Ramboll have joined forces in a bid to find answers. Their joint project will develop a life cycle analysis (LCA) framework for Finnish road conditions using artificial intelligence. This framework will, for example, help reduce waste from road construction and help design road systems with lower emissions. The LCA framework will incorporate a range of climatic factors unique to Finland, which are often not considered in typical LCA studies. The knowledge created in this project can be used to inform decision-making and the development of a sustainable road infrastructure. Industry representatives will gain access to a practical application that can deliver accurate environmental impact assessments in various project contexts. The results will be shared openly thereby contributing to the development of more sustainable road infrastructure globally and especially in the Nordics.
Logistics service providers increasingly involved in circular business models
Project title:
Sustainable Innovation for Growth: Exploring circular business models for a logistics service provider
Approved funding:
203 099 €
Applicant:
Hanken School of Economics
Industrial partner:
Posti
“TIA funding is a great way to pool the resources of a research institute and a business company.”
Helleke Heikkinen, postdoc researcher
The circular economy is a model to conserve natural resources, reduce emissions, and create sustainable growth. Logistics companies have a critical role in advancing circular economy solutions in that their supply chains and business models provide opportunities to extend the life cycle of products. However, theoretical understanding of the role of supply chain management and logistics in the circular economy is still in its infancy. This collaboration between Hanken School of Business and Posti will explore how logistics service providers can become enablers and value creators in circular business models. Business model experiments will be conducted in a real market environment with customers and partner companies. The project will employ the design science research method, the results of which are directly applicable in company strategies. The Principal Investigator for the project is Anna Aminoff.
Richer understanding of forest management chains brings more coordinated forest-related objectives
Project title:
Advanced ecosystem models in multiobjective use of forest resources: More raw material and better ecosystem services from every hectare (AEMES)
Approved funding:
190 068 €
Applicant:
University of Helsinki
Industrial partner:
Metsähallitus Metsätalous
“We’ve been working in forest management science and peatland forestry to develop new calculation methods that can support decision-making in multiobjective forest management. I’m an associate professor in silviculture and in this discipline it’s important that all new methods are put to effective use in practical forestry. TIA funding creates a unique and close link of cooperation between the university and the business partner.”
Marjo Palviainen, Principal investigator
Forests are loaded with both environmental and economic expectations. Attempts to reconcile these diverse objectives may create conflicts and undermine the public acceptability of forestry. This joint project between the University of Helsinki and Metsähallitus is geared to promoting multiobjective forest management and use. It focuses simultaneously on wood production, climate impacts, nutrient loads on waterways, and biodiversity. One of the project’s outputs will be a new tool for comparing different types of forest management chains. A better understanding of these chains will allow for more effective planning and increased wood production while reducing adverse environmental impacts. The scientific information produced by the project will help to support more informed decision-making, and the so-called ecosystem models developed in the project and the related machine learning and optimization applications will be widely available in forest planning, environmental technology, consulting companies, and in the wider society.
Accurate understanding of forest soil properties contributes to better forest management
Project title:
GeoAI explained soil mapping of Finnish forests
Approved funding:
233 470 €
Applicant:
University of Helsinki
Industrial partner:
Arbonaut
“All scientists relish the prospect of seeing their results put into practical use in the field.”
Jori Uusitalo, Principal investigator
The properties of forest soil are a crucial determinant of what type of forest management yields the best results. Accurate identification of the soil type helps in selecting the most appropriate tree species, assessing the regenerative capacity of forest soil, and determining the passability of the soil during different seasons. Tailoring forest management measures to suit each site helps to improve carbon sequestration, reduce environmental damage, and ultimately increase the public acceptability of forestry. This joint project between the University of Helsinki and Arbonaut will develop a deep-learning based method for producing accurate forecasts of forest soil properties for use by all forestry operators. It will also explore how best to visualize data on soil properties for different types of decision-making situations in forest management.
New screening tool for dementia risk
Project title:
Towards real-world neuroscience approaches: Mobile brain-body imaging (MoBI) for predicting dementia risk
Approved funding:
284 649 €
Applicant:
Aalto University
Industrial partner:
Bittium Biosignals
“Funding from the Finnish Research Impact Foundation offers a unique opportunity for Research and Technological Development by bridging the needs and expertise between academia and industry. The funding process is competitive and overall very straightforward.”
Shrikanth Kulashekhar, postdoc researcher
Memory disorders have significant economic, social, and indirect treatment costs. Even though memory disorders develop gradually over time, they are hard to predict with existing medical methods. This collaboration between Aalto University and Bittium Biosignals is aimed at developing an early dementia risk screening tool for the ageing population. Its focus is to study mild cognitive impairment (MCI), i.e. the intermediate state between normal brain ageing and memory disorder. About half of the people with MCI progress to dementia, especially Alzheimer’s disease. The project makes use of mobile brain-body imaging (MoBI), which allows data collection in people’s everyday natural environment, and computational modelling, which improves diagnostic sensitivity. In addition to dementia risk screening, the methods developed in the project will contribute to diagnostic tools for other neurological disorders, such as Parkinson’s disease and post-traumatic stress disorder (PTSD). The Principal Investigator for the project is Hanna Renvall.
