SeeTrue is a leader in modern computer vision (CV) and machine learning (ML) practices.
The Algorithms team is in charge of creating cutting edge algorithmic solutions aimed to automatically detect a wide variety of threats within X-ray and CT security scans. These solutions will help the existing (manual) analysis/detection processes become faster and more accurate.
As a researcher on the team, you will get a chance to work alongside some of the best minds in the field and implement the latest ML and CV algorithms, in a multidisciplinary and dynamic environment.
Deep Learning Expert Position
Upstream Security is looking for a Deep Learning Expert to participate in unique research related to the mobility domain.
Leveraging on top of troves of data from ongoing engagements with world's top vehicle manufacturers, we are working on a revolutionary data platform addressing high impact problems relating to predictive maintenance, car fleet management and more. All while, contributing to Upstream's innovative cybersecurity AI.
Working with data sources of various origins, we offer a great opportunity for professional growth, a genuine state-of-the-art problem domain and a high impact work environment.
As such, we are looking for a talented researcher, MSc (4+ years of industry experience) or PhD (2+ years), with a rich background in ML and (particularly) deep learning research, good communication skills and a demonstrable ability to translate real world problems to the mathematical domain.
Some of the subjects we're interested in:
* state-space embedding
* multivariate time series
* unsupervised / weakly supervised learning framework
* language models
* graph algorithms
Join our talented team and take a major role in one of today’s most interesting and sought-after industries.
About Upstream Security
Upstream Security is a cloud-based data platform purpose-built for connected vehicles and smart mobility services. Upstream’s platform fuses machine learning, data normalization and digital twin profiling technologies. The result is unparalleled cybersecurity, quality assurance, and predictive maintenance insights, readily available and seamlessly integrated into the customer cloud. Upstream is privately funded by Alliance Ventures (Renault, Nissan, Mitsubishi), Volvo Group, Hyundai, Nationwide Insurance, Salesforce Ventures, CRV, Glilot Capital Partners and Maniv Mobility.
The Foundations of Deep Learning Lab at Tel Aviv University's School of Computer Science is looking for excellent research students to help develop a mathematical theory behind deep learning.
Deep learning is experiencing unprecedented success in recent years, delivering state of the art performance in a multitude of application domains. However, despite its extreme popularity and the vast attention it is receiving, our formal understanding of deep learning is limited. Its application in practice is based primarily on conventional wisdom, trial-and-error, and intuition, often leading to suboptimal results (compromising not only effectiveness, but also safety, privacy and/or fairness).
The Foundations of Deep Learning Lab at Tel Aviv University's School of Computer Science is developing a mathematical theory behind deep learning, with the aim of shedding light on existing empirical findings, and more importantly, leading to principled methods that bring forth improved performance and new capabilities. The lab is headed by Prof. Nadav Cohen, and regularly publishes in top tier machine learning venues (e.g. NeurIPS, ICML, ICLR). Its research is highly mathematical, but also includes extensive empirical evaluations that support theory. For more information please visit: https://www.cohennadav.com/.
We are looking for:
You, an excellent mathematically inclined research student, to join us, and help crack open the black box of deep learning. Typical entry to the lab is at MSc level, with the option of pursuing a subsequent PhD if there is mutual interest. Entry at PhD level is also possible, but only in exceptional cases. If interested in applying, please verify that you meet the criteria below, and if so, include in your application CV and grade transcripts.
Prospective MSc students:
* BSc from a well-known university, with GPA of at least 95.0/100 (or equivalent), in one of the following disciplines: (i) Mathematics; (ii) Mathematics & Computer Science; (iii) Mathematics & Electrical Engineering; or (iv) Mathematics & Physics.
* Successful completion of introductory course in machine learning (Tel Aviv University's course #0368323501 or equivalent)
* Solid Python programming skills
* Willingness and ability to devote full-time to research
* High degree of independence, work ethic and creativity
* Experience with deep learning frameworks (e.g. TensorFlow or PyTorch)
* Professional (industry) experience in machine learning
Prospective PhD students:
In addition to the requirements above, applicants interested in joining at PhD level are expected to meet at least one of the following:
* Proven track record in machine learning research (with publication in top-tier venues)
* Advanced coursework and research in either of the following: Statistics, Optimization, Dynamical Systems, Numerical Analysis, Quantum Physics or Quantum Computing.
ML researchers are wanted
1. Application: Analysis of automotive signals for anomalies, fault detection and isolation
2. Responsibilities: Conduct end-to-end applied research including review of the prior art, establishing research plan, implementing PoCs and production-grade models
3. Hard (“must”) requirements:
A degree in exact science
Deep understanding of ML/DL concepts and models
Proficiency in: Python, PySpark, TensorFlow, PyTorch
At least 5 year of ML/DL model development experience
Soft (“nice-to-have”) requirements
D. In Computer Science
Experience in: GANs , VAEs and XAI methods
Experience with signals, time series, anomalies, RNN/LSTM models
Experience with big data (tools and models)- distributed ML
Applications Welcome for fully funded PhD position in Explainable AI and Machine Learning at the School of Informatics, University of Edinburgh. This is a Fully funded PhD position at a world leading research centre in AI. Israeli candidates should be stellar students with a BSc or a MSc in relevant fields. Student can divide time between Edinburgh and Israel. Further details at below link.
Prospera is an AgriTech company that develops intelligent solutions for farmers to grow crops more efficiently.
The company develops both hardware and software solutions that collect and analyze worldwide multi-sensor data with state-of the-art machine learning algorithms. We develop algorithmic solutions for irrigation optimization, pest and disease detection (crop protection), fertilization optimization and much more!
We are now looking for a data scientist with a specialty in computer vision!
Come and join our data science team. Put your skills to solve real world problems, develop state-of-the-art deep learning algorithms combining multi-spectral images with sensor data. Deal with data collected worldwide on a daily basis. Be part of a strong and growing team of algorithm researchers.
M.Sc./Ph.D. – in Computer Science / Mathematics / Physics with specialization in solving computer vision problems, or equivalent (3+ years) industry experience.
2+ years of hands on experience solving deep learning computer vision problems.
Strong background in machine learning and deep learning.
Strong technical skills.
Experience with cloud computing frameworks.
Ability to initiate and lead machine learning projects end to end.
Passionate about data!
We seek a highly motivated postdoctoral researcher for a cutting-edge deep learning (DL) research sponsored by Total Exploration & Production Research & Technology, USA. The research is held at Israel and includes visiting periods at Total (Houston, USA). The postdoctoral researcher will develop novel DL algorithms for solving complex inverse imaging problems. Topics of interest include: DL for 3D seismic inversion, joint Compressed Sensing and DL for seismic imaging, Physics and PDE guided DL architectures, Neural Architecture Search (NAS). We offer a highly competitive salary, and utilization of world-class High-Performance Computing (HPC) resources. For more details contact Dr. Amir Adler, E-mail: firstname.lastname@example.org, Homepage: https://amiradler.mit.edu
Cybord develops technologies that stop counterfeit, defective, and malicious electronic components from getting assembled into products during the manufacturing process. We use computer vision, deep learning algorithms and our global component database.
We are looking for an R&D manager with the following talents:
Shibumi-AI is now full remote, and we are recruiting!
We are looking for a data scientist, with CV expertise, for a strong and diverse team. There is also an option for a part-time position.
We are looking for people who love, live, and breathe data science and understand the challenges of the field.
Python programming at a very high level
Expereince in deep learning computer vision projects
Shibumi-AI is a data science solution company from Tel Aviv.
We help companies to solve data-related tasks and develop ML related features
So if you are the kind of person who likes to learn new domains, solve problems, and develop production-ready solutions, this might fit.
For continuing its innovation and developing its core products, PlaySight is looking for a skilled image processing software engineer to join its team. The role will consist in improving the current production algorithms and continue further in research and development for new products. The position is open to both image processing experts with good C/C++ development skills and C/C++ advanced developers with good image processing knowledge.
THE CANDIDATE WOULD IDEALLY
EXPERIENCE IN THE FOLLOWING CONCEPTS IS A PLUS