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Keywords: AI  or Machine learning  or High Performance Computing 


WEBINAR: High performance bioinformatics: submitting your best NCMAS application

This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021.

Bioinformaticians are increasingly turning to specialised compute infrastructure and...

Keywords: Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS

WEBINAR: High performance bioinformatics: submitting your best NCMAS application https://dresa.org.au/materials/webinar-high-performance-bioinformatics-submitting-your-best-ncmas-application-ee80822f-74ac-41af-a5a4-e162c10e6d78 This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021. Bioinformaticians are increasingly turning to specialised compute infrastructure and efficient, scalable workflows as their research becomes more data intensive. Australian researchers that require extensive compute resources to process large datasets can apply for access to national high performance computing facilities (e.g. Pawsey and NCI) to power their research through the National Computational Merit Allocation Scheme (NCMAS). NCMAS is a competitive, merit-based scheme and requires applicants to carefully consider how the compute infrastructure and workflows will be applied.  This webinar provides life science researchers with insights into what makes a strong NCMAS application, with a focus on the technical assessment, and how to design and present effective and efficient bioinformatic workflows for the various national compute facilities. It will be followed by a short Q&A session. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. High performance bioinformatics: submitting your best NCMAS application - slides (PDF and PPTX): Slides presented during the webinar   Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/HeFGjguwS0Y Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS
WEBINAR: Getting started with deep learning

This record includes training materials associated with the Australian BioCommons webinar  ‘Getting started with deep learning’. This webinar took place on 21 July 2021.

Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces deep...

Keywords: Deep learning, Neural networks, Machine learning

WEBINAR: Getting started with deep learning https://dresa.org.au/materials/webinar-getting-started-with-deep-learning-986aa2d2-594a-4a7f-836c-44d6e9d5d017 This record includes training materials associated with the Australian BioCommons webinar  ‘Getting started with deep learning’. This webinar took place on 21 July 2021. Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces deep learning ‘in a nutshell’ and provides tips on which concepts and skills you will need to know to build a deep learning application. The presentation also provides pointers to various resources you can use to get started in deep learning. The webinar is followed by a short Q&A session. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Getting Started with Deep Learning - Slides (PDF): Slides used in the presentation   Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/I1TmpnZUuiQ Melissa Burke (melissa@biocommons.org.au) Deep learning, Neural networks, Machine learning
WEBINAR: Pro tips for scaling bioinformatics workflows to HPC

This record includes training materials associated with the Australian BioCommons webinar ‘Pro tips for scaling bioinformatics workflows to HPC’. This webinar took place on 31 May 2023.

Event description 

High Performance Computing (HPC) infrastructures offer the computational scale and...

Keywords: Bioinformatics, Workflows, HPC, High Performance Computing

WEBINAR: Pro tips for scaling bioinformatics workflows to HPC https://dresa.org.au/materials/webinar-pro-tips-for-scaling-bioinformatics-workflows-to-hpc-9f2a8b90-88da-433b-83b2-b1ab262dd9df This record includes training materials associated with the Australian BioCommons webinar ‘Pro tips for scaling bioinformatics workflows to HPC’. This webinar took place on 31 May 2023. Event description  High Performance Computing (HPC) infrastructures offer the computational scale and efficiency that life scientists need to handle complex biological datasets and multi-step computational workflows. But scaling workflows to HPC from smaller, more familiar computational infrastructures brings with it new jargon, expectations, and processes to learn. To make the most of HPC resources, bioinformatics workflows need to be designed for distributed computing environments and carefully manage varying resource requirements, and data scale related to biology.   In this webinar, Dr Georgina Samaha from the Sydney Informatics Hub, Dr Matthew Downton from the National Computational Infrastructure (NCI) and Dr Sarah Beecroft from the Pawsey Supercomputing Research Centre help you navigate the world of HPC for running and developing bioinformatics workflows. They explain when you should take your workflows to HPC and highlight the architectural features you should make the most of to scale your analyses once you’re there. You’ll hear pro-tips for dealing with common pain points like software installation, optimising for parallel computing and resource management, and will find out how to get access to Australia’s National HPC infrastructures at NCI and Pawsey.  Materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Pro-tips_HPC_Slides: A PDF copy of the slides presented during the webinar. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/YKJDRXCmGMo Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Workflows, HPC, High Performance Computing
WEBINAR: AlphaFold: what's in it for me?

This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023.

Event description 

AlphaFold has taken the scientific world by storm with the ability to accurately predict the...

Keywords: Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning

WEBINAR: AlphaFold: what's in it for me? https://dresa.org.au/materials/webinar-alphafold-what-s-in-it-for-me-4d1ea222-4240-4b68-b9ae-7769ac664ee0 This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023. Event description  AlphaFold has taken the scientific world by storm with the ability to accurately predict the structure of any protein in minutes using artificial intelligence (AI). From drug discovery to enzymes that degrade plastics, this promises to speed up and fundamentally change the way that protein structures are used in biological research.  Beyond the hype, what does this mean for structural biology as a field (and as a career)? Dr Craig Morton, Drug Discovery Lead at the CSIRO, is an early adopter of AlphaFold and has decades of expertise in protein structure / function, protein modelling, protein – ligand interactions and computational small molecule drug discovery, with particular interest in anti-infective agents for the treatment of bacterial and viral diseases. Craig joins this webinar to share his perspective on the implications of AlphaFold for science and structural biology. He will give an overview of how AlphaFold works, ways to access AlphaFold, and some examples of how it can be used for protein structure/function analysis. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/4ytn2_AiH8s Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning
Accelerating skills development in Data science and AI at scale

At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...

Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material

Accelerating skills development in Data science and AI at scale https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale-2d8a65fa-f96e-44ad-a026-cfae3f38d128 At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally. The talk will also cover our approach as outlined below •        Combined survey of gaps in skills and trainings for Data science and AI •        Provide seats to partners •        Share associate instructors/helpers/volunteers •        Develop combined training materials •        Publish a repository of open source trainings •        Train the trainer activities •        Establish a network of volunteers to deliver trainings at their local regions Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community. Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together. contact@ardc.edu.au AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Monash University - University of Queensland training partnership in Data science and AI

We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning,...

Keywords: data skills, training partnerships, data science, AI, training material

Monash University - University of Queensland training partnership in Data science and AI https://dresa.org.au/materials/monash-university-university-of-queensland-training-partnership-in-data-science-and-ai-8082bf73-d20f-4214-ad8c-95123e25a36c We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning, visualisation, and computing tools, we have established a series of over 20 workshops over the year where either Monash or QCIF hosts the event for some 20-40 of their researchers and students, while some 5 places are offered to participants from the other institution. In the longer term we aim to share material developed at one institution and have trainers present it at the other. In this talk we will describe the many benefits we have found to this approach including access to a wider range of expertise in several rapidly developing fields, upskilling of trainers, faster identification of emerging training needs, and peer learning for trainers. contact@ardc.edu.au data skills, training partnerships, data science, AI, training material