לוח משרות דרושים מתאים גם לסטודנטים

Required V&V SPECT Reliability Intern
Job Description Summary
Responsible for running various verification activities on PET/SPECT medical products (PET: Omni-Total Body, Omni-Legend, and IB (Installed based): DMI/DIQ) and/or (SPECT: StarGuide GX, and IB (Installed based): Maverick/Aurora), where our medical devices covers multi-disciplinary aspects from SW/HW, electronics, mechanics, physics, image quality and radiation - which is safety for users and monitored by a tag all the time.
Job Description:
Work closely with verification & development teams
Non-hybrid, partial position on sites (Haifa & Tirat Hacarmel) - Min. 50% position
Ability to work 3 nightly shifts per week as min. (22:00-07:00)
Ability to work on Friday morning shift and/or Saturday evening shift as needed

We are looking for a Product Intern to join the MI site in MATAM and become part of our team, helping us develop innovative medical solutions.
This is an excellent opportunity for Masters students in Biomedical Engineering who want to gain hands-on experience in the world of product management.
Job Description
What does the role include?
Conducting market and product research
Representing the customers voice in decision‑making processes
Supporting product strategy, work‑plan mapping, and performance tracking
Collaborating with marketing, development, manufacturing, and sales teams
Taking part in real projects that impact the medical field.

we are looking for a Global Planner.
The Global Planner & Floor Controller Student is responsible for planning, scheduling, and monitoring global production and material flows to ensure on-time delivery and operational efficiency. They coordinate between production sites, logistics, procurement, and warehousing to balance capacity, manage constraints, and maintain execution visibility. The role drives floor control activities, tracks work orders, and ensures alignment between planning and real-time factory performance.
Location: Kiryat Gat
Key Responsibilities:
Plan and oversee raw material (RM) requirements in alignment with production plans and forecasts, issue PR, and follow up on the supply plan.
Ensure material availability and timely supply to support production schedules
Collaborate with procurement, logistics, and production teams to ensure smooth and efficient material flow
Maintain and update production-related data, including inventory levels, shortages, and delivery schedules
Analyze data across two ERP systems to identify gaps, discrepancies, and improvement opportunities
Manage raw materials (RM) from receipt and quality release through transfer to the tolling site and final consumption
Ensure alignment and accuracy between internal records and toller stock levels, managed across separate ERP systems
Identify discrepancies, conduct root cause analysis, and drive resolution of issues

we are looking for a PhD Machine Learning Research Intern.
As a Machine Learning Research intern in Tel-Aviv, you will have the opportunity to tackle real world problems by pushing the boundaries of the state-of-the-art, with the goal of publishing your work.
You will join us for a 3-month internship (preferred start date: May) focused on Data-Centric AI. In this project, you will tackle the "glass ceiling" of NLU performance: inherent ambiguity in annotation guidelines and label taxonomies. You will move beyond traditional noise reduction to investigate why human annotators disagree and how these disagreements corrupt "ground truth," directly influencing how we evaluate and improve state-of-the-art models.
Key Job Responsibilities and Duties:
Survey the Landscape: Conduct a comprehensive literature review to synthesize current approaches to data ambiguity, identifying the strengths and limitations of existing methods in handling label noise and taxonomy gaps.
Innovate & Design: Devise novel techniques and metrics to detect, quantify, and resolve inherent ambiguities within NLP datasets and annotation guidelines.
Experiment & Validate: Design and execute rigorous experiments to evaluate your proposed methods, measuring their impact on model reliability and ground truth accuracy.
Publish Findings: Summarize your conclusions and contribute to writing a research paper with the aim of submitting to a top-tier NLP conference (e.g., ACL, EMNLP).
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