PhD/MSc students

Aran Lab, Technion

Computational graduate students and postdoctoral fellows

The Aran Lab integrates multidimensional biomedical data — including genomics and clinical data — to advance precision medicine and improve therapeutic strategies. The core themes of the lab are:

Developing computational methods to understand cellular heterogeneity in complex tissues.

Incorporating cutting-edge technologies (including single-cell RNA-seq and spatial transcriptomics) to study cellular dynamics in the tumor-microenvironment affecting response to immunotherapies.

Investigating real-world evidence and developing machine-learning models to improve clinical decision-making.

The lab is affiliated with the Faculties of Biology and Computer Science and the Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering at the Technion – Israel Institute of Technology, Haifa, Israel.

For more information, please visit

We are seeking motivated students to develop and study novel approaches in translational bioinformatics, or the application of analytic and interpretive methods to optimize the transformation of

data of many types into proactive, predictive, preventative, and participatory health.

Ideal candidates will have:

  • Strong background in one or more of the following fields: computational biology, bioinformatics, biostatistics, clinical informatics, data science and machine learning.
  • Background in molecular biology, medicine or pharmacology will be a strong plus.
  • Prior experience with genetic, transcriptomic, drug, or clinical databases, machine-learning, deep-learning, text-mining and knowledge representation is a plus.
  • Strong problem-solving skills, creative thinking, and the ability to build new software tools as needed are required.

ARpalus is a deep-tech startup revolutionising the world of retail through real-time product-recognition on edge-devices using a unique combination of deep-learning and 3D augmented-reality.
We're looking for the best computer-vision deep-learning researcher to join our team and help us further boost our current (working!) technology.
We're now in exciting days of successful pilots and projects, in Israel and abroad, and we're looking for a super-talented researcher, who's fun to work with, to join the celebration 😉

– At-least M.Sc. in relevant faculty and topic, preferably from one of the top universities.
– At-least 1 year of hands-on experience with Deep-learning Python frameworks, preferably dealing with object detection and recognition.
– Fast learner, energetic with passion to computer-vision challenges, Can-Do attitude, team-player and fun to work with.

Nice to Have:
– Significant experience with Python OpenCV, for classic-CV and deep-learning.
– Familiarity with 3D data, depth sensing, and augmented-reality spatial signals (e.g. SLAM).
– Experience with optimising existing given DL models (e.g. YOLO), through applying architecture improvements and augmentations (beyond parameter tuning).
– Experience with Python based ML dev-ops and automations, e.g. Dynamic deployment of training sessions on high-scale Dockers on GCP cloud and continuously evaluating the resulting models.

Data Scientist

Bank Hapoalim

For team that "wraps" the bank's model developers, checks and gives recommendations for future work; We are looking for a creative worker with self-taught ability and charisma.
The work includes reading articles, analytic advisory, performing comprehensive tests (explainabilty, overfit test, calibration tests and stability) on the model and theoretical tests driving to conclusions for new methodological directions to the model developers like changing metrics, algorithms, encodings and so on.
The role is very open and enabling, but it also has a frontal part with the need to present and motivate the findings

Job Description
Validation and research with regard to models for rating credit, collection, detection, prevention and investigation of fraud and embezzlement (anti-fraud), money laundering and models in the field of sales and marketing using mathematical / statistical / algorithmic tools, including reconstruction and development of models for the purpose of benchmarking (challenger models). The work is done vis a vis large databases and a variety of business information.
• Development of risk quantification methods and research in order to enhance the methodology
• Investigate the information used as input and in favor of calibrating the parameters for models
• Providing professional opinions and producing executive management reports
• Existence of intensive work interfaces with the bank's stakeholders, subsidiaries and branches abroad, the Supervisor of Banks, accountants and auditors,legal advisors leading consulting service providers in Israel and abroad and more.

• Master's degree in scientific degree – a significant advantage
• Experience working with large DBs and working with SQL – required
• Experience in developing models – required
• Python SAS R MATLAB – required
• written and ability to express at an advanced level
• Proficiency in English

Deep Learning Expert

Upstream Security

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.

PhD research student

Tel-Aviv University

The new Robotics lab at the School of Mechanical Engineering at Tel-Aviv University aims to increase access to robots in domestic and industrial environments to improve the quality of life. The lab, led by Dr. Avishai Sintov, increase the capabilities of robots in various tasks while putting a strong emphasis on the simplicity of the hardware. Such approach enables the use of a low-cost hardware and minimal sensing while implementing advanced algorithms of motion planning and artificial intelligence.

For more information about the Robotic lab:

The Robotics lab invites applications for a PhD student position in the area of Human-Robot collaboration. The research will be multidisciplinary including motion planning under uncertainty, machine learning and wearable sensing.


1. Applicants should have M.Sc. in Mechanical Engineering, Electrical Engineering, Computer Science or other close enough field.

2. Experience in machine learning.

3. Python and c++ programming.

4. Passion for robotic research.

5. Experience working with ROS and robotic hardware is an advantage.

Interested applicants should send their CV, list of publications and grade transcripts to Dr. Sintov.

We are looking for a Senior Data Scientist to join our group. We are looking for a person which can take full responsibility and lead projects in the team.

How your day to day will look like?

  • Evaluate and build various models used by our trading teams.
  • Develop new predictive models and optimize systems to enhance trading performance.
  • Collaborate with other teams to turn experimental models into production-ready systems.

What should you bring with you?

  • 4+ years of experience working with predictive and probabilistic models.
  • Excellent hands-on SQL skills.
  • Solid experience and skill in quantitative programming including strong proficiency in R or Python.
  • Experience in management / leading projects.
  • Excellent quantitative problem solving skills.
  • Ability to initiate and lead research projects from idea to productization.
  • An excellent foundation of quantitative theory coupled with an ability to build real-world models and analytical tools.
  • Driven, organized, and able to work on independent research and real-world problem solving with efficiency and accuracy.
  • Curiosity and a desire to continue learning new processes and technologies.
  • B.A / B.Sc. / M.Sc. in Statistics, macroeconomics, Physics, mathematics or equivalent.
  • Experience in FinTech, Algo Trade – a big advantage

Research Student

Foundations of Deep Learning Lab, Tel Aviv University


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.

About us:

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:

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/DL Researcher


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

Computer Vision Researcher

Prospera Technologies

Prospera Technologies

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!

Job Title

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.

Skills & Experience

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!

Post-Doctoral Researcher: Deep Learning for Inverse Problems

Braude College of Engineering & Total USA

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:, Homepage:

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