Jos olet hakenut AI-DOC tohtorikoulutuspilottiin kuuluvaa väitöskirjatutkijan tehtävää 2.4.2024 mennessä, hakemuksesi otetaan huomioon Aalto yliopiston organisoimassa yliopistojen yhteisrekrytoinnissa. Jyväskylän yliopiston järjestämässä haussa otamme huomioon kaikki Jyväskylän yliopistolle 30.4.2024 mennessä jätetyt hakemukset riippumatta siitä, onko sama hakija jättänyt hakemuksen myös Aallon organisoimaan yhteishakuun.
Lippulaiva: FCAI
Tutkimusala: Statistics and Artificial Intelligence
Koordinaattori: Aalto-yliopisto
Partnerit: Helsingin yliopisto, Tampereen yliopisto, Oulun yliopisto, Jyväskylän yliopisto, Turun yliopisto, LUT-yliopisto, Itä-Suomen yliopisto, Vaasan yliopisto, Åbo Akademi, Teknologian tutkimuskeskus VTT Oy, Geologian tutkimuskeskus, CSC - Tieteen tietotekniikan keskus
Väitöskirjatutkijan tehtävät JYUssa: 7
Artificial intelligence (AI), the fastest developing general-purpose technology, is a key area for Finland’s competitiveness: every field and business needs AI expertise. Finnish AI research is among the best in Europe in selected fields of research, and we have a favorable operating environment for the creation, development, and utilization of AI technologies.
The doctoral program rests on two interlinked pillars: 1) strong fundamental research in AI as a necessary condition for applying AI responsibly and competitively, and 2) a set of application areas of high scientific quality and wide impact in industry and society.
1) Fundamental AI:
Fundamental AI methods are the core of the research activities and the cornerstone in all application areas. Fundamental AI encompasses probabilistic AI for verifiable and uncertainty-aware model building, simulation-based inference for efficient and interpretable reasoning capabilities, data-efficient deep learning, privacy-preserving and secure AI, interactive AI for collaborative AI tools, autonomous AI, statistics, and decision-making. Widely applicable goals of the fundamental AI are AI-assisted decision-making, design and modeling.
Keywords: Artificial Intelligence, Causal Inference, Collaborative AI and human modeling, Machine Learning, Statistics
2) Application areas:
AI in Communications, Signal Processing and Engineering
The area covers a wide range of advanced methods in communications technology, statistical methods in signal processing, and analysis of images, video, speech, and audio signals. Industries are currently employing AI methods in numerous research and development tasks, e.g., in product design and predictive maintenance.
Keywords: Array signal processing, Computer vision, Perception, Sensors, Wireless communications, Autonomous systems, Energy systems, Machine automation
AI in Language and Speech Technology
The area covers various aspects of natural language processing. It includes language model-based technologies, and speech recognition and analysis methods. Special focus is given to cross-lingual transfer and technologies for smaller languages, like Finnish and Swedish that are structurally very different from e.g. English and need a separate approach.
Keywords: Foundation models, Human language technology, Large language models, Speech recognition
AI in Society and Business
The area focuses on social and ethical aspects of AI, including the preconditions of trustworthy and socially acceptable. AI and the consequences of use of AI. It brings together AI research and human sciences to better understand how AI works in organizations and society. Another dimension of the area is AI and data-based methods in economics.
Keywords: AI in business operations, AI in technology and society, Education, Trust & ethics
The PhD topics are integrated into ongoing research in supervisors’ groups to provide peer support and help in getting the first scientific paper out quickly. Teaming up in fundamental AI research and application areas, and across them, provides peer support to PhD students. Companies and research institutes are an integral part of the program and they will provide future jobs for the PhDs. The planned activities of AI-DOC include biannual seminars for the whole network, entrepreneurship training, summer schools and research seminars. There will be mobility possibilities for the PhD students.
AI-DOC is associated with