What do we do?

You can join the group of any of the 6 academics below. Each academic has offered a number of topics they are recruiting into.

Dima Damen: Professor of Computer Vision with research interests in egocentric vision, video understanding and fine-grained action understanding.

• Problems using EPIC-KITCHENS (+VISOR, EPIC Fields) or Ego4D datasets
• Long-Tail Video Understanding
• Fine-Grained Video Descriptions
• Audio-visual fine-grained action recognition, localisation or retrieval

Peter Flach: Professor of Artificial intelligence with research interests in evaluation and improvement of machine learning models, mining highly structured data, and human-centred AI.

• Classifier calibration
• Uncertainty representation and propagation
• Knowledge-intensive AI
• Explainability and interpretability

Majid Mirmehdi: Professor of Computer Vision with research interests in human and animal behaviour understanding and medical image/volume analysis

• Human action understanding and assessment, e.g. in healthcare for action quality scores
• Animal action analysis and understanding using camera-trap, drone for other footage
• Segmentation, Classification, and Prediction in medical images and volumes

Raul Santos-Rodriguez: Associate Professor in Data Science and AI with research interests in the foundations of (human-centric) machine learning and its applications to healthcare and climate science.

• Explainability, transparency and fairness
• Weakly supervised learning
• Human visual perception in machine learning
• Human/agent interaction and collaboration

Michael Wray: Assistant Professor of Computer Vision with research interests in video understanding and Natural Language Processing.

• Understanding Biases in Vision Language Models
• Video Moment Retrieval and Video Corpus Moment Retrieval for Long Videos
• Fine-grained Vision-Language Retrieval
• Compositionality for Video-Language models

Zahraa S. Abdallah: Assistant Professor in Data science and Machine Learning with research interest in time series and its healthcare applications and learning from multiple modalities.

• Time series analysis (classification, clustering, explainability)
• Adaptive and active learning
• Genomic data analysis e.g., protein analysis for early detection of cancer
• Data fusion and multi-modalities for combining various types of data sources

Telmo Silva Filho: Assistant Professor in Data Science with research interests in evaluation of machine learning models, explainability, latent-variable models, and medical applications of computer vision.

• Explainable evaluation, i.e. when/why is a model expected to fail?
• Latent-variable models for evaluation
• Segmentation and synthetic generation of medical images

Tilo Burghardt: Associate Professor in Computer Science with research interests in animal biometrics, imageomics and applications of computer vision to animal welfare, farming, and conservation

• Deep learning for the detection of animal species, individuals, and morphological traits
• Recognition of animal poses, behaviours, and social configurations
• Integration of methods in computer vision, taxonomics, genetics, and ecology
• Autonomous visual navigation of conservation drones and related robotic platforms

What do we offer?

Applicants will be selected based on their academic excellence, previous experiences and provided references. We have a limited number of 10 positions throughout the program annually

You are expected to be in Bristol for the majority of your visit's duration. During your research visit, you will be supervised by your selected faculty member, and integrated within their research group. You will have access to our excellent resource of GPUs (Blue Crystal 4) to run any experiments, a university of bristol email account with access to our PGR resources and a desk allocated for the duration of your visit.

Additionally, you will have opportunities to present your work and attend talks by the various MaVi researchers. A social program over weekends will give you the opportunity to explore Bristol and its surroundings, guided by one of our friendly PGR students. Note that any expenses for the social activities are not covered by the program. Note that you need to bring your own laptop – machines will not be provided as part of the program.