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). The ideal candidate will have: A PhD in environmental science or closely related discipline by the start date of the appointment Broad understanding of eco-evolutionary optimality concepts and modelling
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that is developing novel robotic solutions for practical, real-world settings. Current approaches to many perception and autonomy challenges use simplifying assumptions and controlled environments. Our team
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development tools such as version control. Please see https://scicomp.aalto.fi/rse/become-a-rse/ for more information on what kind of skills we value - or more precisely what you are likely to learn. Good
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to deliver industry-relevant tools that enable optimal design and operation of hydrogen technologies in real-world application. The successful candidate will work at the intersection of multi-disciplinary
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Role Description Department We are seeking an experienced mathematical modeller. Our group is developing a range of advanced genetics-based methods for controlling mosquito-borne diseases, based
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of plant invasiveness, mutualisms among invading organisms in forests, risks and benefits of non-native trees in forestry, social perceptions of non-native species in forests, economic optimization of forest
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prototype (MIDAS) that integrates AI-based modules with optimisation engines to support low-carbon, cost-optimal datacentre microgrid design. To manage prototyping of the software platform - overseeing build
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studies within the hydrogen research hub (HI-ACT) funded by EPSRC. The project seeks to deliver industry-relevant tools that enable optimal design and operation of hydrogen technologies in real-world
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particular emphasis on kinetic Monte Carlo approaches, and in software development, including version control (Git or similar). Experience in ab initio methods and specifically calculations of excited
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strong potential o Proficiency in Python and/or R programming languages o Experience working in high-performance computing (HPC) environments o Command line proficiency and BASH scripting