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CVPR 2024 Career Website

Here we highlight career opportunities submitted by our Exhibitors, and other top industry, academic, and non-profit leaders. We would like to thank each of our exhibitors for supporting CVPR 2024. Opportunities can be sorted by job category, location, and filtered by any other field using the search box. For information on how to post an opportunity, please visit the help page, linked in the navigation bar above.

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Redmond, Washington, United States


Overview We are seeking a highly skilled and passionate Research Scientist to join our Responsible & OpenAI Research (ROAR) team in Azure Cognitive Services.

As a Research Scientist, you will play a key role in advancing the field of Responsible Artificial Intelligence (AI) to ensure safe releases of the rapidly advancing AI technologies, such as GPT-4, GPT-4V, DALL-E 3 and beyond, as well as to expand and enhance our standalone Azure AI Content Safety Service.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities Conduct cutting-edge research to develop Responsible AI definitions, methodologies, algorithms, and models for both measurement and mitigation of AI risks. Stay abreast of the latest advancements in the field and contribute to the scientific community through publications at top venues. Contribute to the development of Responsible AI policies, guidelines, and best practices and ensure the practical implementation of these guidelines within various AI technology stacks across Microsoft, promoting a consistent approach to Responsible AI. Enable the safe release of new Azure OpenAI Service features, expand and enhance the Azure AI Content Safety Service with new detection technologies. Develop innovative approaches to address AI safety challenges for diverse customer scenarios. Other: Embody our Culture and Values


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Captions is the AI-powered creative studio. Millions of creators around the world have used Captions to make their video content stand out from the pack and we're on a mission to empower the next billion.

Based in NYC, we are a team of ambitious, experienced, and devoted engineers, designers, and marketers. You'll be joining an early team where you'll have an outsized impact on both the product and company's culture.

We’re very fortunate to have some the best investors and entrepreneurs backing us, including Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, Lenny Rachitsky, and more.

Check out our latest milestone and our recent feature on the TODAY show and the New York Times.

** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) **

Responsibilities:

Conduct research and develop models to advance the state-of-the-art in generative computer vision technologies, with a focus on creating highly realistic digital faces, bodies, avatars.

Strive to set new standards in the realism of 3D digital human appearance, movement, and personality, ensuring that generated content closely resembles real-life scenarios.

Implement techniques to achieve high-quality results in zero-shot or few-shot settings, as well as customized avatars for different use cases while maintaining speed and accuracy.

Develop innovative solutions to enable comprehensive customization of video content, including the creation of digital people, modifying scenes, and manipulating actions and speech within videos.

Preferred Qualifications:

PhD in computer science (or related field) and/ or 5+ years of industry experience.

Strong academic background with a focus on computer vision and transformers, specializing in NeRFs, Gaussian Splatting, Diffusion, GANs or related areas.

Publication Record: Highly relevant publication history, with a focus on generating or manipulating realistic digital faces, bodies, expressions, body movements, etc. Ideal candidates will have served as the primary author on these publications.

Expertise in Deep Learning: Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar, with hands-on experience in designing, training, and deploying neural networks for multimodal tasks.

Strong understanding of Computer Science fundamentals (algorithms and data structures).

Benefits: Comprehensive medical, dental, and vision plans

Anything you need to do your best work

We’ve done team off-sites to places like Paris, London, Park City, Los Angeles, Upstate NY, and Nashville with more planned in the future.

Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Please note benefits apply to full time employees only.


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Redmond, Washington, United States


Overview We are seeking a Principal Research Engineer to join our organization and help improve steerability and control Large Language Models (LLMs) and other AI systems. Our team currently develops Guidance, a fully open-source project that enables developers to control language models more precisely and efficiently with constrained decoding.

As a Principal Research Engineer, you will play a crucial role in advancing the frontier of constrained decoding and imagining new application programming interface (APIs) for language models. If you’re excited about links between formal grammars and generative AI, deeply understanding and optimizing LLM inference, enabling more responsible AI without finetuning and RLHF, and/or exploring fundamental changes to the “text-in, text-out” API, we’d love to hear from you. Our team offers a vibrant environment for cutting-edge, multidisciplinary research. We have a long track record of open-source code and open publication policies, and you’ll have the opportunity to collaborate with world-leading experts across Microsoft and top academic institutions across the world.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities Develop and implement new constrained decoding research techniques for increasing LLM inference quality and/or efficiency. Example areas of interest include speculative execution, new decoding strategies (e.g. extensions to beam search), “classifier in the loop” decoding for responsible AI, improving AI planning, and explorations of attention-masking based constraints. Re-imagine the use and construction of context-free grammars (CFG) and beyond to fit Generative AI. Examples of improvements here include better tools for constructing formal grammars, extensions to Earley parsing, and efficient batch processing for constrained generation. Consideration of how these techniques are presented to developers – who may not be well versed in grammars and constrained generation -- in an intuitive, idiomatic programming syntax is also top of mind. Design principled evaluation frameworks and benchmarks for measuring the effects of constrained decoding on a model. Some areas of interest to study carefully include efficiency (token throughput and latency), generation quality, and impacts of constrained decoding on AI safety. Publish your research in top AI conferences and contribute your research advances to the guidance open-source project. Other

Embody our Culture and Values


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You will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work with different research teams and squads across multiple areas led by our Director of Science, Prof. Vittorio Ferrari, and directly impact our solutions that are used worldwide by over 55,000 businesses.

If you have seen the full ML lifecycle from ideation through implementation, testing and release, and you have a passion for large data, large model training and building solutions with clean code, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.


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ASML US, including its affiliates and subsidiaries, bring together the most creative minds in science and technology to develop lithography machines that are key to producing faster, cheaper, more energy-efficient microchips. We design, develop, integrate, market and service these advanced machines, which enable our customers - the world’s leading chipmakers - to reduce the size and increase the functionality of their microchips, which in turn leads to smaller, more powerful consumer electronics. Our headquarters are in Veldhoven, Netherlands and we have 18 office locations around the United States including main offices in Chandler, Arizona, San Jose and San Diego, California, Wilton, Connecticut, and Hillsboro, Oregon.

ASML’s Optical Sensing (Wafer Alignment Sensor and YieldStar) department in Wilton, Connecticut is seeking a Design Engineer to support and develop complex optical/photonic sensor systems used within ASML’s photolithography tools. These systems typically include light sources, detectors, optical/electro-optical components, fiber optics, electronics and signal processing software functioning in close collaboration with the rest of the lithography system. As a design engineer, you will design, develop, build and integrate optical sensor systems.

Role and Responsibilities Use general Physics, Optics, Software knowledge and an understanding of the sensor systems and tools to develop optical alignment sensors in lithography machines Have hands-on sills of building optical systems (e.g. imaging, testing, alignment, detector system, etc.) Have strong data analysis sills to evaluate sensor performance and troubleshooting Leadership:

Lead executing activities for determining problem root cause, execute complex tests, gather data and effectively communicate results on different levels of abstraction (from technical colleagues to high level managers) Lead engineers in various competencies (e.g. software, electronics, equipment engineering, manufacturing engineering, etc.) in support of feature delivery for alignment sensors Problem Solving: Troubleshooting complex technical problems Develop/debug data signal processing algorithms Develop and execute test plans in order to determine problem root cause Communications/Teamwork: Draw conclusions based on the input from different stakeholders Capability to clearly communicate the information on different level of abstraction Programming: Implement data analysis techniques into functioning MATLAB codes Optimization skills GUI building experience Familiarly with LabView and Python Some travel (up to 10%) to Europe, Asia and within the US can be expected


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Inria (Grenoble), France


human-robot interaction, machine learning, computer vision, representation learning

We are looking for highly motivated students joining our team at INRIA. This project will take place in close collaboration between Inria team THOTH and the multidisciplinary institute in artificial intelligence (MIAI) in Grenoble

Topic: Human-robot systems are challenging because the actions of one agent can significantly influence the actions of others. Therefore, anticipating the partner's actions is crucial. By inferring beliefs, intentions, and desires, we can develop cooperative robots that learn to assist humans or other robots effectively. In this project we are in particular interested in estimating human intentions to enable collaborative tasks between humans and robots such as human-to-robot and robot-to-human handovers.

Contact pia.bideau@inria.fr The thesis will be jointly supervised by Pia Bideau (THOTH), Karteek Alahari (THOTH) and Xavier Alameda Pineda (RobotLearn).


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The Autonomy Software Metrics team is responsible for providing engineers and leadership at Zoox with tools to evaluate the behavior of Zoox’s autonomy stack using simulation. The team collaborates with experts across the organization to ensure a high safety bar, great customer experience, and rapid feedback to developers. The metrics team is responsible for evaluating the complete end-to-end customer experience through simulation, evaluating factors that impact safety, comfort, legality, road citizenship, progress, and more. You’ll be part of a passionate team making transportation safer, smarter, and more sustainable. This role gives you high visibility within the company and is critical for successfully launching our autonomous driving software.


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London


Who we are Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly.

Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale

Where you will have an impact We're looking for an experienced Applied Scientist with expertise in Neural Radiance Fields (NeRFs) and Gaussian Splatting to join our Vision & Graphics team and advance our innovative neural simulator, Ghost Gym. This role is central to improving Ghost Gym's capabilities, utilizing state-of-the-art neural rendering techniques to craft photorealistic 4D worlds. You'll be at the forefront of developing and applying groundbreaking research to generate thousands of simulated scenarios. These scenarios are critical for training, testing, and debugging our end-to-end AI driving models, contributing significantly to the creation of safe and reliable AI driving technology. Your work will focus on improving the efficiency, realism, and dynamism of our simulations, especially for dynamic and outdoor environments, pushing the limits of current photorealistic visualization technologies.

Challenges you will own Conducting cutting-edge research in NeRFs, Gaussian splatting, and related technologies, with a focus on solving real-world challenges in 3D rendering Developing and implementing algorithms for efficient, high-quality 3D scene reconstruction and rendering, particularly for dynamic and outdoor environments Collaborating with cross-functional teams to integrate research findings into scalable, production-level solutions Staying abreast of the latest developments in the field, evaluating and incorporating state-of-the-art techniques into our workflows Potentially finding opportunities to publish research findings in top-tier journals and conferences, contributing to the scientific community and establishing Wayve as a leader in the field What you will bring to Wayve Essential Proven track record of research in NeRFs, Gaussian splatting, or closely related areas, demonstrated through publications or deployed applications Strong programming skills in Python with experience in deep learning frameworks such as PyTorch Solid foundation in mathematics and physics underlying 3D graphics and rendering techniques Excellent problem-solving skills and the ability to work independently as well as in a team environment Demonstrated ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment

Desirable Experience with dynamic scene reconstruction and rendering, particularly in outdoor environments Familiarity with parallel computing, GPU programming, and optimization techniques PhD or MSc in Computer Science, Computer Engineering, or a related field, with a focus on computer graphics, computer vision, or machine learning What we offer you The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact Competitive compensation and benefits A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day


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Mountain View


Who we are Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly.

Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale

Where you will have an impact We are looking for an experienced Research Engineer to help us in our journey to scale end-to-end neural networks for autonomous driving. You’ll be working across our research team to build, integrate, test and scale algorithms, tools, and machine learning solutions for autonomous driving.

What you will bring to Wayve 5+ years of software engineering experience in an industrial research environment Passion to work in a team on research ideas that have real world impact Strong software engineering experience in Python and other relevant languages (especially C++ and CUDA) Ideally with direct experience working in at least one of computer vision, robotics, simulation, graphics, large language models Ideally with several years working on large-scale machine learning algorithms and systems BS, MS, or above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience

What we offer you The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact Competitive compensation Fully employer-covered medical, dental and vision insurance! Further benefits such as catered lunch, yummy snacks, and variety of drinks, life insurance, employer contributed retirement account, therapy, yoga, office-wide socials and much more. A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day This is a full-time role based in our office in California. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We also operate core working hours so you can be where you need to be for family and loved ones too. Teams determine the routines that work best for them.


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A postdoctoral position is available in Harvard Ophthalmology Artificial Intelligence (AI) Lab (https://ophai.hms.harvard.edu) under the supervision of Dr. Mengyu Wang (https://ophai.hms.harvard.edu/team/dr-wang/) at Schepens Eye Research Institute of Massachusetts Eye and Ear and Harvard Medical School. The start date is flexible, with a preference for candidates capable of starting in August or September 2024. The initial appointment will be for one year with the possibility of extension. Review of applications will begin immediately and will continue until the position is filled. Salary for the postdoctoral fellow will follow the NIH guideline commensurate with years of postdoctoral research experience.

In the course of this interdisciplinary project, the postdoc will collaborate with a team of world-class scientists and clinicians with backgrounds in visual psychophysics, engineering, biostatistics, computer science, and ophthalmology. The postdoc will work on developing statistical and machine learning models to improve the diagnosis and prognosis of common eye diseases such as glaucoma, age-related macular degeneration, and diabetic retinopathy. The postdoc will have access to abundant resources for education, career development and research both from the Harvard hospital campus and Harvard University campus. More than half of our postdocs secured a faculty position after their time in our lab.

For our data resources, we have about 3 million 2D fundus photos and more than 1 million 3D optical coherence tomography scans. Please check http://ophai.hms.harvard.edu/data for more details. For our GPU resources, we have 22 in-house GPUs in total including 8 80-GB Nvidia H100 GPUs, 10 48-GB Nvidia RTX A6000 GPUs, and 4 Nvidia RTX 6000 GPUs. Please check http://ophai.hms.harvard.edu/computing for more details. Our recent research has been published in ICCV 2023, ICLR 2024, CVPR 2024, IEEE Transactions on Medical Imaging, and Medical Image Analysis. Please check https://github.com/Harvard-Ophthalmology-AI-Lab for more details.

The successful applicant will:

  1. possess or be on track to complete a PhD or MD with background in computer science, mathematics, computational science, statistics, machine learning, deep learning, computer vision, image processing, biomedical engineering, bioinformatics, visual science and ophthalmology or a related field. Fluency in written and spoken English is essential.

  2. have strong programming skills (Python, R, MATLAB, C++, etc.) and in-depth understanding of statistics and machine learning. Experience with Linux clusters is a plus.

  3. have a strong and productive publication record.

  4. have a strong work ethic and time management skills along with the ability to work independently and within a multidisciplinary team as required.

Your application should include:

  1. curriculum vitae

  2. statement of past research accomplishments, career goal and how this position will help you achieve your goals

  3. Two representative publications

  4. contact information for three references

The application should be sent to Mengyu Wang via email (mengyu_wang at meei.harvard.edu) with subject “Postdoctoral Application in Harvard Ophthalmology AI Lab".


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Location Multiple Locations


Description

Members of our team are part of a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems. Our members contribute technology deployed worldwide by partnering with our business teams across mobile, compute, automotive, cloud, and IOT. We also perform and publish state-of-the-art research on a wide range of topics in machine-learning, ranging from general theory to techniques that enable deployment on resource-constrained devices. Our research team has demonstrated first-in-the-world research and proof-of-concepts in areas such model efficiency, neural video codecs, video semantic segmentation, federated learning, and wireless RF sensing (https://www.qualcomm.com/ai-research), has won major research competitions such as the visual wake word challenge, and converted leading research into best-in-class user-friendly tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet). We recently demonstrated the feasibility of running a foundation model (Stable Diffusion) with >1 billion parameters on an Android phone under one second after performing our full-stack AI optimizations on the model.

Role responsibility can include both, applied and fundamental research in the field of machine learning with development focus in one or many of the following areas:

  • Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. large language models, deep generative models (VAE, Normalizing-Flow, ARM, etc), Bayesian deep learning, equivariant CNNs, adversarial learning, diffusion models, active learning, Bayesian optimizations, unsupervised learning, and ML combinatorial optimization using tools like graph neural networks, learned message-passing heuristics, and reinforcement learning.

  • Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for model compression, quantization, architecture search, and kernel/graph compiler/scheduling with or without systems-hardware co-design.

  • Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, causal and language-based reasoning.

  • Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond. The use cases can broadly include computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design

  • Design, develop & test software for machine learning frameworks that optimize models to run efficiently on edge devices. Candidate is expected to have strong interest and deep passion on making leading-edge deep learning algorithms work on mobile/embedded platforms for the benefit of end users.

  • Research, design, develop, enhance, and implement different components of machine learning compiler for HW Accelerators.

  • Design, implement and train DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).


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Location Seattle, WA


Description Amazon's Compliance Shared Services (CoSS) is looking for a smart, energetic, and creative Sr Applied Scientist to extend and invent state-of-the-art research in multi-modal architectures, large language models across federated and continuous learning paradigms spread across multiple systems to join the Applied Research Science team in Seattle. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale that increase automation accuracy and coverage, and extend and invent new research as a key author to deliver re-usable foundational capabilities for automation.

You will analyze and process large amounts of image, text and tabular data from product detail pages, combine them with additional external and internal sources of multi-modal data, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms in federated and continuous learning modes that can be integrated and launched across multiple systems. You will partner with engineers and product managers across multiple Amazon teams to design new ML solutions implemented across worldwide Amazon stores for the entire Amazon product catalog.


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ASML US, including its affiliates and subsidiaries, bring together the most creative minds in science and technology to develop lithography machines that are key to producing faster, cheaper, more energy-efficient microchips. We design, develop, integrate, market and service these advanced machines, which enable our customers - the world’s leading chipmakers - to reduce the size and increase the functionality of their microchips, which in turn leads to smaller, more powerful consumer electronics. Our headquarters are in Veldhoven, Netherlands and we have 18 office locations around the United States including main offices in Chandler, Arizona, San Jose and San Diego, California, Wilton, Connecticut, and Hillsboro, Oregon.

The Advanced Development Center at ASML in Wilton, Connecticut is seeking an Optical Data Analyst with expertise processing of images for metrology process development of ultra-high precision optics and ceramics. The Advanced Development Center (ADC) is a multi-disciplinary group of engineers and scientists focused on developing learning loop solutions, proto-typing of next generation wafer and reticle clamping systems and industrialization of proto-types that meet the system performance requirements.

Role and Responsibilities The main job function is to develop image processing, data analysis and machine learning algorithm and software to aid in development of wafer and reticle clamping systems to solve challenging engineering problems associated with achieving nanometer (nm) scale precision. You will be part of the larger Development and Engineering (DE) sector – where the design and engineering of ASML products happens.

As an Optical Data Analyst, you will: Develop/improve image processing algorithm to extract nm level information from scientific imaging equipment (e.g. interferometer, SEM, AFM, etc.) Integrate algorithms into image processing software package for analysis and process development cycles for engineering and manufacturing users Maintain version controlled software package for multiple product generations Perform software testing to identify application, algorithm and software bugs Validate/verify/regression/unit test software to ensure it meets the business and technical requirements Use machine learning models to predict trends and behaviors relating to lifetime and manufacturing improvements of the product Execute a plan of analysis, software and systems, to mitigate product and process risk and prevent software performance issues Collaborate with the design team in software analysis tool development to find solutions to difficult technical problems in an efficient manner Work with database structures and utilize capabilities Write software scripts to search, analyze and plot data from database Support query code to interrogate data for manufacturing and engineering needs Support image analysis on data and derive conclusions Travel (up to 10%) to Europe, Asia and within the US can be expected


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Canberra/Australia


We are looking for new outstanding PhD students for the upcoming scholarship round (application is due on 31st August 2024) at the Australian National University (ANU is ranked #30 in the QS Ranking 2025) or possibly at another Australian universities.

We are looking for new PhD students to work on new problems that may span over (but are not limited to) "clever" adapting of Foundation Models, LLMs, diffusion models (LORAs etc.,), NERF, or design of Graph Neural Networks, design of new (multi-modal) Self-supervised Learning and Contrastive Learning Models (masked models, images, videos, text, graphs, time series, sequences, etc. ) or adversarial and/or federated learning or other contemporary fundamental/applied problems (e.g., learning without backprop, adapting FMs to be less resource hungry, planning and reasoning, hyperbolic geometry, protein property prediction, structured output generative models, visual relation inference, incremental/learning to learn problems, low shot, etc.)

To succeed, you need an outstanding publication record, e.g., one or more first-author papers in venues such CVPR, ICCV, ECCV, AAAI, ICLR, NeurIPS, ICML, IJCAI, ACM KDD, ACCV, BMVC, ACM MM, IEEE. Trans. On Image Processing, CVIU, IEEE TPAMI, or similar (the list is non-exhaustive). Non-first author papers will also help if they are in the mix. Some patents and/or professional experience in Computer Vision, Machine Learning or AI are a bonus. You also need a good GPA to succeed.

We are open to discussing your interests and topics, if you reach out, we can discuss what is possible. Yes, we have GPUs.

If you are interested, reach out for an informal chat with Dr. Koniusz. I am at CVPR if you want to chat?): piotr.koniusz@data61.csiro.au (or piotr.koniusz@anu.edu.au, www.koniusz.com)


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