Job Description Summary As a Research Engineer involved in the design of electrical machines, you will work in a collaborative team environment. You will be contributing to the development of advanced machine system concepts as well as their implementation for application to aircraft engine systems, power generation, and electric and hybrid vehicle applications. As part of a multi-disciplinary team, you will contribute to the planning, development, and transition of technologies from concept to products and/or services for GE Aerospace internal and external clients.

GE Aerospace Research will continue to play a vital role in supporting the industry through a historic recovery while shaping the future of flight. We invent the future of flight, lift people up and bring them home safely. Our commitment to lead the industry, to keep safe the flying public and the armed forces, and to lift up one another and our communities, remains our north star. Our purpose is what ties us to one another and gives meaning to our work.

Roles and Responsibilities

Work with customers to identify key system requirements.

Determine electrical machine (generators, motors, power delivery, and accessories') requirements by studying system and customer requirements.

Use system simulation tools, such as MATLAB, Simulink, and PLECS, to validate and refine control algorithms for a wide array of electric machines to ensure the system will perform in a manner consistent with the requirements.

Integrate the output of finite element analysis and other machine design software to determine and implement machine parameters within the system model.

Work closely with the electrical machine design team to make sure the physical machine meets requirements.

Develop and implement test procedures for electrical machine systems and document performance characteristics.

Deliver effective presentations, reports, and publications to Global Research, GE Businesses, government agencies, professional societies, and peer-reviewed journals.

Required Qualifications

PHD in Electrical Engineering or related field, with primary focus in controls applied to electric machines.

In-depth knowledge of electrical machines including electromagnetic, thermal as well as mechanical technology aspects.

Experience in a wide variety of machine topologies

Expertise in simulation tools such as finite elements, MATLAB (Simulink) and others such as PLECS.

US Citizenship required

Must be willing to work out of an office located in Niskayuna, NY

Must be 18 years or older

You must submit your application for employment on the careers page at www.gecareers.com to be considered.

Desired Characteristics

Experience in Automotive Hybrid Electrical or Aerospace Systems.

Strong interpersonal skills.

Strong analytical skills.

Ability to work across all functions/levels as part of a global team.

Ability to work under pressure and meet deadlines.

Excellent written and verbal communication skills.

Strong ties to the external technical community.

Entrepreneurial inclination

The base pay range for this position is 80,000 - 150,000 USD Annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary. This posting is expected to close on July 12, 2024

Location Madrid, ESP

Description At Amazon, we are committed to being the Earth’s most customer-centric company. The International Technology group (InTech) owns the enhancement and delivery of Amazon’s cutting-edge engineering to all the varied customers and cultures of the world. We do this through a combination of partnerships with other Amazon technical teams and our own innovative new projects.

You will be joining the Tools and Machine learning (Tamale) team. As part of InTech, Tamale strives to solve complex catalog quality problems using challenging machine learning and data analysis solutions. You will be exposed to cutting edge big data and machine learning technologies, along to all Amazon catalog technology stack, and you'll be part of a key effort to improve our customers experience by tackling and preventing defects in items in Amazon's catalog.

We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading machine learning solutions. We strongly value your hard work and obsession to solve complex problems on behalf of Amazon customers.

Overview We are seeking an exceptionally talented Postdoctoral Research Fellow to join our interdisciplinary team at the forefront of machine learning, computer vision, medical image analysis, neuroimaging, and neuroscience. This position is hosted by the Stanford Translational AI (STAI) in Medicine and Mental Health Lab (PI: Dr. Ehsan Adeli, https://stanford.edu/~eadeli), as part of the Department of Psychiatry and Behavioral Sciences at Stanford University. The postdoc will have the opportunity to directly collaborate with researchers and PIs within the Computational Neuroscience Lab (CNS Lab) in the School of Medicine and the Stanford Vision and Learning (SVL) lab in the Computer Science Department. These dynamic research groups are renowned for groundbreaking contributions to artificial intelligence and medical sciences.

Project Description The successful candidate will have the opportunity to work on cutting-edge projects aimed at building large-scale models for neuroimaging and neuroscience through innovative AI technologies and self-supervised learning methods. The postdoc will contribute to building a large-scale foundation model from brain MRIs and other modalities of data (e.g., genetics, videos, text). The intended downstream applications include understanding the brain development process during the early ages of life, decoding brain aging mechanisms, and identifying the pathology of different neurodegenerative or neuropsychiatric disorders. We use several public and private datasets including but not limited to the Human Connectome Project, UK Biobank, Alzheimer's Disease Neuroimaging Initiative (ADNI), Parkinson’s Progression Marker Initiative (PPMI), Open Access Series of Imaging Studies (OASIS), Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA), Adolescent Brain Cognitive Development (ABCD), and OpenNeuro.

Key Responsibilities Conduct research in machine learning, computer vision, and medical image analysis, with applications in neuroimaging and neuroscience. Develop and implement advanced algorithms for analyzing medical images and other modalities of medical data. Develop novel generative models. Develop large-scale foundation models. Collaborate with a team of researchers and clinicians to design and execute studies that advance our understanding of neurological disorders. Mentor graduate students (Ph.D. and MSc). Publish findings in top-tier journals and conferences. Contribute to grant writing and proposal development for securing research funding.

Qualifications PhD in Computer Science, Electrical Engineering, Neuroscience, or a related field. Proven track record of publications in high-impact journals and conferences including ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, MICCAI, Nature, and JAMA. Strong background in machine learning, computer vision, medical image analysis, neuroimaging, and neuroscience. Excellent programming skills in Python, C++, or similar languages and experience with ML frameworks such as TensorFlow or PyTorch. Ability to work independently and collaboratively in an interdisciplinary team. Excellent communication skills, both written and verbal.

Benefits Competitive salary and benefits package. Access to state-of-the-art facilities and computational resources. Opportunities for professional development and collaboration with leading experts in the field. Participation in international conferences and workshops. Working at Stanford University offers access to world-class research facilities and a vibrant intellectual community. The university provides numerous opportunities for interdisciplinary collaboration, professional development, and cutting-edge innovation. Additionally, being part of Stanford opens doors to a global network of leading experts and industry partners, enhancing both career growth and research impact.

Apply For full consideration, send a complete application via this form: https://forms.gle/KPQHPGGeXJcEsD6V6

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

Seattle, WA or Costa Mesa, CA

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

The Vehicle Autonomy (Robotics) team at Anduril develops aerial and ground-based robotic systems. The team is responsible for taking products like Ghost, Anvil, and our Sentry Tower from paper sketches to operational systems. We work in close coordination with specialist teams like Perception, Autonomy, and Manufacturing to solve some of the hardest problems facing our customers. We are looking for software engineers and roboticists excited about creating a powerful robotics stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications.

WHAT YOU'LL DO -Write and maintain core libraries (frame transformations, targeting and guidance, etc.) that all robotics platforms at Anduril will use -Own feature development and rollout for our products - recent examples include: building a Software-in-the-Loop simulator for our Tower product, writing an autofocus control system for cameras, creating a distributed over IPC coordinate frame library, redesigning the Pan-Tilt controls to accurately move heavy loads -Design, evaluate, and implement sensor integrations that support operation by both human and autonomous planning agents -Work closely with our hardware and manufacturing teams during product development, providing quick feedback that contributes to the final hardware design

REQUIRED QUALIFICATIONS -Strong engineering background from industry or school, ideally in areas/fields such as Robotics, Computer Science, Software Engineering, Mechatronics, Electrical Engineering, Mathematics, or Physics -5+ years of C++ or Rust experience in a Linux development environment -Experience building software solutions involving significant amounts of data processing and analysis -Ability to quickly understand and navigate complex systems and established code bases -Must be eligible to obtain and hold a US DoD Security Clearance.

PREFERRED QUALIFICATIONS -Experience in one or more of the following: motion planning, perception, localization, mapping, controls, and related system performance metrics. -Understanding of systems software (kernel, device drivers, system calls) and performance analysis

Location Seattle, WA

Description To help a growing organization quickly deliver more efficient features to Prime Video customers, Prime Video’s READI organization is innovating on behalf of our global software development team consisting of thousands of engineers. The READI organization is building a team specialized in forecasting and recommendations. This team will apply supervised learning algorithms for forecasting multi-dimensional related time series using recurrent neural networks. The team will develop forecasts on key business dimensions and recommendations on performance and efficiency opportunities across our global software environment.

As a member of the team, you will apply your deep knowledge of machine learning to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them for customers, where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into designs with development teams and developing ready-to-use learning models. You consistently bring strong, data-driven business and technical judgment to decisions.

Location Bellevue, WA

Description Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale.

This role is for the AFT AI team which has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. The team is comprised of scientists, who develop machine learning and computer vision solutions, analytics, who evaluate the expected business impact for a project and the performance of these solutions, and software engineers, who provide necessary support such as annotation pipelines and machine learning library development.

We are looking for an Applied Scientist with expertise in computer vision. You will work alongside other CV scientists, engineers, product managers and various stakeholders to deploy vision models at scale across a diverse set of initiatives. If you are a self-motivated individual with a zeal for customer obsession and ownership, and are passionate about applying computer vision for real world problems - this is the team for you.

Location Multiple Locations

Description Today, more intelligence is moving to end devices, and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile, Qualcomm envisions making AI ubiquitous—expanding beyond mobile and powering other end devices, machines, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, and 5G to make this a reality.

Job Purpose & Responsibilities As a member of Qualcomm’s ML Systems Team, you will participate in two activities: Development and evolution of ML/AI compilers (production and exploratory versions) for efficient mappings of ML/AI algorithms on existing and future HW Analysis of ML/AI algorithms and workloads to drive future features in Qualcomm’s ML HW/SW offerings

Key Responsibilities: Contributing to the development and evolution of ML/AI compilers within Qualcomm Defining and implementing algorithms for mapping ML/AI workloads to Qualcomm HW Understanding trends in ML network design, through customer engagements and latest academic research, and how this affects both SW and HW design Creation of performance-driven simulation components (using C++, Python) for analysis and design of high-performance HW/SW algorithms on future SoCs Exploration and analysis of performance/area/power trade-offs for future HW and SW ML algorithms Pre-Silicon prediction of performance for various ML algorithms Running, debugging and analyzing performance simulations to suggest enhancements to Qualcomm hardware and software to tackle compute and system memory-related bottlenecks · Successful applications will work in cross-site, cross-functional teams.

Requirements: Demonstrated ability to learn, think and adapt in fast changing environment Detail-oriented with strong problem-solving, analytical and debugging skills Strong communication skills (written and verbal) Strong background in algorithm development and performance analysis is essential The following experiences would be significant assets: Strong object-oriented design principles Strong knowledge of C++ Strong knowledge of Python Experience in compiler design and development Knowledge of network model formats/platforms (eg. Pytorch, Tensorflow, ONNX) is an asset. On-silicon debug skills of high-performance compute algorithms · Knowledge of algorithms and data structures Knowledge of software development processes (revision control, CD/CI, etc.) · Familiarity with tools such as git, Jenkins, Docker, clang/MSVC Knowledge of computer architecture, digital circuits and event-driven transactional models/simulators

Gothenburg, Sweden

This fully-funded PhD position offers an opportunity to delve into the area of geometric deep learning within the broader landscape of machine learning and 3D computer vision. As a candidate, you'll have the chance to develop theoretical concepts and innovative methodologies while contributing to real-world imaging applications. Moreover, you will enjoy working in a diverse, collaborative, supportive and internationally recognized environment.

The PhD project centers on understanding and improving deep learning methods for 3D scene analysis and 3D generative diffusion models. We aim to explore new ways of encoding symmetries in deep learning models in order to scale up computations, a necessity for realizing truly 3D generative models for general scenes. We aim to explore the application of these models in key problems involving novel view synthesis and self-supervised learning.

If you are interested and present at CVPR, then feel free to reach out to Prof. Fredrik Kahl, head of the Computer Vision Group.

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".

The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.

※Location※ South Korea Seoul / Pangyo

※Description※ 1) Deep learning compression and optimization - Development of algorithms for compression and optimization of deep learning networks - Perform deep learning network embedding (requires understanding of HW platform)

2) AD vision recognition SW - Development of deep learning recognition technology based on sensors such as cameras - Development of pre- and post-processing algorithms and function output - Development of optimization of image recognition algorithm

3) AD decision/control SW - Development of information-based map generation technology recognized by many vehicles - Development of learning-based nearby object behavior prediction model - Development of driving mode determination and collision prevention function of Lv 3 autonomous driving system

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.

We are seeking a highly motivated candidate for a fully funded postdoctoral researcher position to work in 3D computer graphics and 3D computer vision.

The successful candidate will join the 3D Graphics and Vision research group led by Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College Dublin, Ireland to work on topics related to generative AI in the 3D domain. The School of Computer Science and Statistics at Trinity College Dublin is a collegiate, friendly, and research-intensive centre for academic study and research excellence. The School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS Subject Rankings 2018, 2019, 2020, 2021).

The postdoctoral researcher is expected to conduct fundamental research and publish in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV, SIGGRAPH) and journals (TPAMI, IJCV). Other responsibilities include supporting graduate or undergraduate students with technical guidance and engagement in other research activities such as paper reviews, reading group, workshop organization, etc.

The start date of the position is August 01, 2024. Contract duration is 1 year with the option of renewing for a second year. The successful candidate will require the following skills and knowledge: • PhD in Computer Science or related fields; • Strong tracked records in 3D computer graphics, 3D computer vision; • Hands-on experience in training deep models and generative models is required; • Hands-on experience and relevant skills in computer graphics and computer vision application development such as OpenGL, OpenCV, CUDA, Blender is desirable; • Strong programming skills in C++, Python. Capability in implementing systems from research papers and open-source software. • Additional background in math, statistics, or physics is an advantage.

Applicants should provide the following information: • A comprehensive CV including a full list of publications; • The name and contact details of two referees. One of the referees should be the applicant’s PhD supervisor; • Two representative papers by the applicant. Interested candidates should email their applications to Binh-Son Hua (https://sonhua.github.io) directly. Applications will be reviewed on a rolling basis until the position has been filled.

Location Sunnyvale, CA Bellevue, WA Seattle, WA

Description The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Science Manager with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems.

As an Applied Science Manager with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision.