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- Representation Learning from Sequential Data : Explore the complexities of sequential data to discover new insights and methods for learning representations. Familiarity with state-of-the-art approaches in self-supervised learning from vast unlabeled data corpora of various modalities, efficient training methods, modern Transformer-based architectures, as well as multi-task and multi-objective optimization paradigms will be helpful.
- Learning on Graphs : Explore innovative approaches to graph-based learning, enhancing our understanding and application of relationships and network information. We are seeking candidates who are knowledgeable in modern Graph Neural Networks architectures, and familiar with challenges of learning from massive graph-structured datasets, in particular spatial-temporal graphs.
- Generative Models for Content Generation : Investigate how deep generative models can be utilized to produce creative and varied content, challenging the limits of creativity and efficiency. This area focuses on incorporating aspects of gameplay, including players and level embeddings, to create unique gaming experiences. A background in generative models, multimodality, and zero-shot learning is beneficial.
- Reinforcement Learning for Gameplay : Work with advanced Reinforcement Learning (RL) strategies to transform playtesting, enhancing player experiences with more engaging and dynamic interactions. Candidates with a strong foundation in RL and practical experience with the latest cutting-edge online and offline RL algorithms, especially those related to Decision Transformers, are encouraged to apply. Familiarity with embedding models will be considered an advantage.
- Collaborate with Research Engineers to contribute to research projects aligned with your area of interest.
- Participate in the entire research lifecycle, from problem definition to exploring methodologies, to implementation and evaluation.
- Assist ML Engineers and Data Scientists in developing, testing, and operationalizing machine learning models.
- Document and present research findings and progress within the team and to relevant stakeholders.
- Currently pursuing a MSc or a PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Recent graduates with relevant backgrounds are welcome to apply.
- Strong foundational knowledge in machine learning, data science, and algorithm development.
- Excellent problem-solving skills and the ability to work independently as well as part of a team.
- Having a keen interest in AI research and its application in real-world scenarios, particularly in one or more of the internship themes.
- Knowledge or previous experience in the topic and relevant methodologies covered in the theme is preferred.
- Experienced with programming languages such as Python and proficiency in ML libraries and frameworks.
- Holding a valid authorization to work in Sweden starting from August 2024 for 6 months.
Autumn Internships 2024 - Stockholm, Sverige - King
Beskrivning
Craft:Technology & Development Job Description: AI Labs at King's AI Center of Excellence Join AI Labs, a pioneering applied research team within King's AI Center of Excellence, where innovation and collaboration intersect to solve complex modeling challenges and explore the forefront of machine learning technologies. At AI Labs, we support the business by unlocking opportunities to bring substantial value through state-of-the-art research. Our team focuses on automation at scale for game levels, optimizing player experiences, ensuring AI trustworthiness, and delving into new emerging technologies. Working alongside Research Engineers, ML Engineers, and Data Scientists, you'll contribute to both mid-term and long-term research projects and play a crucial role in developing ML models as part of King's central machine learning initiatives. The Opportunity: For this internship cycle, we are looking for motivated Research Engineer Interns (multiple positions available) who are passionate about the following research themes:
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