Elekta AB (publ)

We don’t just build technology. We build hope for everyone dealing with Cancer. Elekta is shaping the standard of care, together with healthcare providers, by developing precision radiation medicine that brings advanced radiotherapy into routine clinical practice. Our solutions support consistent, efficient and personalized care, addressing evolving patient needs. Through adaptive radiotherapy, precision treatment delivery and integrated workflows, Elekta supports care teams across a range of clinical settings. Each year more than 2 million patients are treated using Elekta solutions across over 130 countries. Elekta is headquartered in Stockholm, Sweden, with over 4,000 employees and offices in more than 40 countries. The company is listed on Nasdaq Stockholm. For more information, visit elekta.com. What You’ll Do At Elekta As a Group Business Controller, you will play a central role in our Group Business Control function, helping provide senior management with clear, reliable financial insights that support informed decision-making. You will lead and coordinate group-wide planning and forecasting, analyse financial performance and key business drivers, and work closely with regions, business lines and the wider finance community. Through strong financial analysis and business partnering, you will help strengthen performance, improve the quality and consistency of reporting, and drive greater cost awareness across the Group. Responsibilities Coordinate the Group budget and forecast cycles, including consolidation, challenging assumptions and explaining changes in outlook. Analyse and quality assure Group financial performance against budget, forecast and prior periods, identifying key revenue, margin, expense and cash drivers. Lead performance reviews with regions and business areas, agree follow-up actions and track progress. Prepare concise financial reports, insights and decision material for senior management and the Board of Directors. Develop Group performance measures, reporting definitions and processes to improve consistency and comparability across the business. Act as a finance business partner to senior stakeholders, providing analysis on costs, strategic initiatives, risks and opportunities. Support a reliable monthly close and contribute financial analysis and quality review to interim, annual and other external reporting. Partner with Finance and IT to improve financial BI applications, data quality and reporting processes. What You’ll Bring Bachelor's degree in finance, economics, industrial engineering or a similar field. At least 5+ years of experience in financial analysis, business planning, forecasting and performance management. Experience with financial reporting, consolidation, planning and BI systems. Ability to translate complex financial information into clear, concise insights and decision material for senior stakeholders. Strong stakeholder management and business partnering skills, with the ability to work effectively across regions, business lines and functions. High attention to detail and sound financial judgement. Ability to challenge assumptions constructively and turn financial analysis into practical recommendations. A collaborative approach and the ability to build effective relationships across a global finance organisation. Fluency in both English and Swedish is preferred. What You’ll Get 30 paid vacation days per year. 4 additional Elekta days off. Defined contribution pension scheme. Private Medical Insurance. Lunch Benefit. Contribution to wellness activities. A collaborative office environment four days a week, working alongside talented colleagues in a supportive and engaging workplace. Application process We look forward to receiving your application. Please submit your CV in English via the “Apply” button. We review applications on an ongoing basis, so we encourage you to apply as soon as possible.

Are you a current Elekta employee? Please click here to apply through our internal career site Find Jobs - Elekta. We don’t just build technology. We build hope for everyone dealing with Cancer. Elekta is shaping the standard of care, together with healthcare providers, by developing precision radiation medicine that brings advanced radiotherapy into routine clinical practice. Our solutions support consistent, efficient and personalized care, addressing evolving patient needs. Through adaptive radiotherapy, precision treatment delivery and integrated workflows, Elekta supports care teams across a range of clinical settings. Each year more than 2 million patients are treated using Elekta solutions across over 130 countries. Elekta is headquartered in Stockholm, Sweden, with over 4,000 employees and offices in more than 40 countries. The company is listed on Nasdaq Stockholm. For more information, visit elekta.com. What You'll Do At Elekta As a Senior Electronics Engineer, you will help develop the Control System for the Leksell Gamma Knife, a safety-critical medical device for precise radiation treatment. The system operates and monitors treatment delivery, patient positioning, imaging integration, safety functions, operator workflows, communication interfaces and embedded mechatronic subsystems. You will work closely with specialists across engineering, production, quality, supply chain and service to solve electronics challenges throughout the product lifecycle. Your work will directly support the reliability and continued development of the Leksell Gamma Knife. Responsibilities Design, develop and update electronic systems, from schematics and detailed design to system-level integration. Verify and troubleshoot electronics, including hands-on laboratory work, measurements and testing. Develop solutions that meet technical, regulatory, EMC and electrical safety requirements. Solve product lifecycle challenges including design improvements, product maintenance, component obsolescence and complaint investigations. Collaborate across R&D, production, quality, service, supply chain and external partners to support electronics from development through production and service. Contribute to technical reviews, risk assessments, development planning, while sharing knowledge and helping shape future electronics solutions for the Leksell Gamma Knife. What You'll Bring M.Sc. degree in Electronics, Mechatronics, Engineering Physics, or a related engineering discipline. At least five years of experience in electronics development, including electronic system design, debugging, verification and hands-on lab work. Experience with analog and digital electronics, EMC, and electrical safety. Experience collaborating within multidisciplinary engineering teams. Strong communication skills and professional proficiency in English. Preferred Qualifications Experience with VHDL. Experience with power electronics. Experience developing medical devices or working in other regulated industries. Experience working with safety-critical products and systems. What You'll Get 30 paid vacation days per year. 4 additional Elekta days off. Defined contribution pension scheme. Private Medical Insurance. Lunch benefit. Contribution to wellness activities. A collaborative office environment where employees work together onsite four days per week. Application Process We look forward to receiving your application. Please submit your CV in English via the Apply button. We review applications on an ongoing basis and encourage you to apply as soon as possible. About Elekta As a leader in precision radiation therapy, Elekta is committed to ensuring every patient has access to the best cancer care possible. We openly collaborate with customers to advance sustainable, outcome-driven and cost-efficient solutions to meet evolving patient needs, improve lives and bring hope to everyone dealing with cancer. To us, it's personal, and our global team of 4,700 employees combine passion, science, and imagination to profoundly change cancer care. We don’t just build technology, we build hope. Elekta is headquartered in Stockholm, Sweden, with offices in more than 120 countries and listed on Nasdaq Stockholm. For more information, visit elekta.com or follow us on LinkedIn, Glassdoor, Twitter, Facebook, Instagram and YouTube.

Are you a current Elekta employee? Please click here to apply through our internal career site Find Jobs - Elekta. We don’t just build technology. We build hope for everyone dealing with Cancer. Elekta is shaping the standard of care, together with healthcare providers, by developing precision radiation medicine that brings advanced radiotherapy into routine clinical practice. Our solutions support consistent, efficient and personalized care, addressing evolving patient needs. Through adaptive radiotherapy, precision treatment delivery and integrated workflows, Elekta supports care teams across a range of clinical settings. Each year more than 2 million patients are treated using Elekta solutions across over 130 countries. Elekta is headquartered in Stockholm, Sweden, with over 4,000 employees and offices in more than 40 countries. The company is listed on Nasdaq Stockholm. For more information, visit elekta.com. Introduction Radiotherapy targets and surrounding anatomy can move during treatment. The Elekta Unity combines an MR scanner with a linear accelerator, enabling anatomy to be visualised during radiation delivery and allowing treatment adaptation based on real-time information. However, there are inherent latencies associated with image acquisition, image processing, data transfer, and motion estimation. To compensate for these latencies, future anatomical motion must be predicted. This project will investigate whether an AI-based approach can improve prediction accuracy at extended prediction horizons. Background Radiotherapy treatments are designed with millimeter precision to ensure that high doses of radiation can be delivered to the target while sparing surrounding healthy tissues and critical anatomical structures. However, both the target and surrounding anatomy may move during treatment due to physiological processes such as respiration, peristalsis, and organ drift. The Elekta Unity can visualise and respond to this motion in real time, improving dosimetric accuracy and therefore improving patient outcomes. The current Automatic Position Management (APM) framework acquires an orthogonal pair of 2D cine images at a rate of 5 Hz. Each image is compared with a reference image using rigid registration to estimate target motion. A prediction engine then extrapolates the observed motion to estimate the target position once all processing steps have been completed. In the future, longer prediction horizons may be required to support more advanced image acquisition strategies, target-tracking approaches, or dose-based interventions. To enable these developments, a prediction algorithm must maintain accuracy while predicting further into the future. AI methods such as recurrent neural networks have shown promise for time-series prediction tasks both within and beyond radiation oncology and will therefore form the primary focus of this investigation. Problem Statement The project will investigate the suitability of AI approaches for motion prediction on the Unity platform through the following objectives: Curate a dataset of target centroid motion from a range of anatomies influenced by respiratory motion using a combination of publicly available datasets and historical MR-Linac treatment data. Establish a benchmark by evaluating the curated dataset using the currently implemented prediction algorithm. Choose a suitable AI model to predict centroid motion at clinically relevant prediction horizons. Adapt the model and train on the data collected. Compare the performance of the proposed approach against the existing prediction algorithm using appropriate quantitative metrics. Output An assessment of the potential benefits of incorporating AI-based motion prediction within the APM framework A curated motion dataset that can support future research and development activities. Prototype software, reproducible processing pipelines, and documentation. A written report and final presentation Who are we looking for? We are looking for a master’s student in medical physics, computer science, applied mathematics, engineering physics, or a related scientific discipline.  Required profile:  Programming experience and the ability to work independently on an exploratory research problem.  A strong scientific or engineering background, including confidence with quantitative analysis.  Desirable experience:  Experience in medical image processing, ideally in Python Experience with AI / deep learning methods Familiarity with radiotherapy, especially the MR-Linac Practicalities Location: Elekta office, Stockholm Supervisor: Ned Goodwin Start date: Flexible About Elekta As a leader in precision radiation therapy, Elekta is committed to ensuring every patient has access to the best cancer care possible. We openly collaborate with customers to advance sustainable, outcome-driven and cost-efficient solutions to meet evolving patient needs, improve lives and bring hope to everyone dealing with cancer. To us, it's personal, and our global team of 4,700 employees combine passion, science, and imagination to profoundly change cancer care. We don’t just build technology, we build hope. Elekta is headquartered in Stockholm, Sweden, with offices in more than 120 countries and listed on Nasdaq Stockholm. For more information, visit elekta.com or follow us on LinkedIn, Glassdoor, Twitter, Facebook, Instagram and YouTube.

Master Thesis Creating Synthetic Motion in MR Images for Evaluation of Novel Approaches to Motion Management on Unity hos Elekta. Plats: Stockholm. Publicerad: Posted 11 Days Ago. Referens: R2026-1570. Ansök via Workday.

Are you a current Elekta employee? Please click here to apply through our internal career site Find Jobs - Elekta. We don’t just build technology. We build hope for everyone dealing with Cancer. Elekta is shaping the standard of care, together with healthcare providers, by developing precision radiation medicine that brings advanced radiotherapy into routine clinical practice. Our solutions support consistent, efficient and personalized care, addressing evolving patient needs. Through adaptive radiotherapy, precision treatment delivery and integrated workflows, Elekta supports care teams across a range of clinical settings. Each year more than 2 million patients are treated using Elekta solutions across over 130 countries. Elekta is headquartered in Stockholm, Sweden, with over 4,000 employees and offices in more than 40 countries. The company is listed on Nasdaq Stockholm. For more information, visit elekta.com. Introduction Leksell Gamma Plan (LGP) is a successful treatment planning system for stereotactic neuro radiotherapy performed by the Leksell Gamma Knife. Both are made by Elekta in Stockholm. LGP is used by neurosurgeons and radio oncologists worldwide to analyse brain imaging and identify targets and choose doses of gamma radiation, as well as planning the application of the required doses to these targets by the Leksell Gamma Knife over a series of one or more treatment fractions. Background An important step in each treatment is correctly determining the position of structures shown in CT/MR brain imaging in a co-ordinate system relative to the machine. A mechanical frame with fiducial marks is firmly attached to the patient’s head prior to imaging, and the marks are visible in the resulting images. The frame is firmly attached to the Gamma Knife during treatment, allowing the correct calculation of positions of structures in the brain in a known co-ordinate system (calculation of the transformation from image co-ordinates to machine co-ordinates is known as registration). Problem Statement Present image registration algorithm for tomographic (MR/CT) images is semi-automatic and we would like to automate it and see if better registration transforms can be found. Output This thesis project aims to: a) Propose and prototype method(s) for fully automatic detection of fiducial marks in MR/CT images. b) Propose and prototype method(s) for fully automatic image registration based on fiducials. c) Propose relevant metric(s) for quality assurance (e.g. mean and max errors). d) Evaluate robustness and accuracy for proposed method(s) compared to current fiducial based registration in LGP (for >100 representative and varying cases). Who are we looking for? Masters student, probably specialized in image handling/graphics. No prior knowledge of Gamma Knife treatment planning is required. Domain experts from Elekta will provide introductions to the relevant aspects of the software architecture and workflow. The student will work closely with experts in software development and clinical applications throughout the project.   Practicalities Location: Elekta office, Stockholm Supervisor: Ethan Palmiere, ethan.palmiere@elekta.com Start date: Early 2027 About Elekta As a leader in precision radiation therapy, Elekta is committed to ensuring every patient has access to the best cancer care possible. We openly collaborate with customers to advance sustainable, outcome-driven and cost-efficient solutions to meet evolving patient needs, improve lives and bring hope to everyone dealing with cancer. To us, it's personal, and our global team of 4,700 employees combine passion, science, and imagination to profoundly change cancer care. We don’t just build technology, we build hope. Elekta is headquartered in Stockholm, Sweden, with offices in more than 120 countries and listed on Nasdaq Stockholm. For more information, visit elekta.com or follow us on LinkedIn, Glassdoor, Twitter, Facebook, Instagram and YouTube.

Master Thesis Usability Evaluation and Modernization Strategy for a Safety-Critical Medical Device User Interface hos Elekta. Plats: Stockholm. Publicerad: Posted 11 Days Ago. Referens: R2026-1485. Ansök via Workday.

Are you a current Elekta employee? Please click here to apply through our internal career site Find Jobs - Elekta. We don’t just build technology. We build hope for everyone dealing with Cancer. Elekta is shaping the standard of care, together with healthcare providers, by developing precision radiation medicine that brings advanced radiotherapy into routine clinical practice. Our solutions support consistent, efficient and personalized care, addressing evolving patient needs. Through adaptive radiotherapy, precision treatment delivery and integrated workflows, Elekta supports care teams across a range of clinical settings. Each year more than 2 million patients are treated using Elekta solutions across over 130 countries. Elekta is headquartered in Stockholm, Sweden, with over 4,000 employees and offices in more than 40 countries. The company is listed on Nasdaq Stockholm. For more information, visit elekta.com. Introduction Cone beam computed tomography (CBCT) is a method of forming a 3D image from a set of X-ray projections. The projections are formed by exposing a subject to a cone-shaped X-ray beam and capturing the photons in a flat-panel detector, similar to the detector of a camera. The subject both attenuates and scatters the X-ray beam, affecting what photons are detected by the detector. Projections are formed from multiple directions. This results in an inverse problem that can be solved to reconstruct a 3D image of the subject. There are efficient algorithms to solve this inverse problem when there is no scattering (FDK or iterative solvers). A common approach to CBCT reconstruction is to estimate the scattering and effectively subtract it from projection images so that these efficient algorithms can be employed for reconstruction. Background At Elekta, we develop products for cancer radiotherapy that use CBCT for imaging and positioning the patient. We are today using an AI model to estimate the scatter component in CBCT images. As an alternative to this, we have developed a physics-based algorithm (patent pending) for estimating scatter. We have made a prototype implementation of this algorithm in 2000 lines of Rust that we call Rainbow. Problem Statement There are several open questions related to our scatter estimates that could be the basis of a master's thesis. What we decide on depends on your interests and our needs. Engineering focus: How do we best evaluate Rainbow’s performance? What subjects do we scan, what metrics do we measure, how do we compare with state-of-the-art AI models? What applications is it suitable for? Physics focus: What improvements can be made to the physical model of Rainbow? We have made several approximations of the scattering and detector physics that can be improved for a more accurate model. This may involve both physics theory and experimental work in our labs. Implementation focus: To be clinically useful, Rainbow needs to run faster. Are there optimizations we can make to the current implementation? How do we efficiently implement this algorithm on a GPU? Math focus: What improvements can be made to the algorithm, such as Monte Carlo variance reduction or methods for accelerating convergence of a numerical solver. Depending on our findings until the start of the master thesis work, we may have other topics related to CBCT reconstruction and scatter estimates. Output The student is expected to write a report that helps us understand the above-mentioned aspects of Rainbow. In the case of investigating various improvements, this should be accompanied by code contributions to Rainbow. In the case of benchmarking Rainbow, the report should be accompanied by scripts for running these benchmarks. Who are we looking for? Preferred Masters education: Physics or Mathematics Required skills: Python programming, good understanding of statistics and numerical methods. Useful skills: X-ray lab work, Rust programming, GPU computing, Monte Carlo simulations Practicalities Location: Forskaren, Hagaplan 4, Stockholm Supervisor: Petter Säterskog, petter.saterskog@elekta.com Start date: Fall 2026 or early spring 2027 About Elekta As a leader in precision radiation therapy, Elekta is committed to ensuring every patient has access to the best cancer care possible. We openly collaborate with customers to advance sustainable, outcome-driven and cost-efficient solutions to meet evolving patient needs, improve lives and bring hope to everyone dealing with cancer. To us, it's personal, and our global team of 4,700 employees combine passion, science, and imagination to profoundly change cancer care. We don’t just build technology, we build hope. Elekta is headquartered in Stockholm, Sweden, with offices in more than 120 countries and listed on Nasdaq Stockholm. For more information, visit elekta.com or follow us on LinkedIn, Glassdoor, Twitter, Facebook, Instagram and YouTube.

Are you a current Elekta employee? Please click here to apply through our internal career site Find Jobs - Elekta. We don’t just build technology. We build hope for everyone dealing with Cancer. Elekta is shaping the standard of care, together with healthcare providers, by developing precision radiation medicine that brings advanced radiotherapy into routine clinical practice. Our solutions support consistent, efficient and personalized care, addressing evolving patient needs. Through adaptive radiotherapy, precision treatment delivery and integrated workflows, Elekta supports care teams across a range of clinical settings. Each year more than 2 million patients are treated using Elekta solutions across over 130 countries. Elekta is headquartered in Stockholm, Sweden, with over 4,000 employees and offices in more than 40 countries. The company is listed on Nasdaq Stockholm. For more information, visit elekta.com. 1 Introduction Cone-beam CT (CBCT) is an imaging technique widely used in radiation therapy for patient positioning and adaptive workflow. 2D projections are acquired from a cone-shaped X-ray beam rotating around the patient, and a 3D image is reconstructed from these projections. The imaging device is mounted directly on the treatment machine, i.e. a linear accelerator (linac), which allows for imaging the patient in the treatment position. However, the acquisition of CBCT images is relatively slow, and patient motion during the scan can lead to image artifacts and reduced image quality. Motion compensation techniques aim to mitigate these effects by estimating and correcting for patient motion during the reconstruction process. This thesis will investigate and prototype motion compensation methods for CBCT imaging in radiation therapy, with the goal of improving image quality and treatment accuracy. 2 Background Respiratory and cardiac motion are the dominant source of motion artifacts in CBCT for radio[1]therapy which cause blurring, streaking and banding artifacts in the reconstructed images (Chen et al., 2004). Currently deployed techniques to mitigate motion artifacts in CBCT include: 1. Breath-hold techniques — The patient suspends respiration during acquisition, ef[1]fectively eliminating motion. However, this approach has significant clinical overhead: it reduces patient comfort, requires trained operator coordination, and is impossible for uncooperative or sedated patients. 2. Respiratory gating (Kincaid Jr. et al., 2013) — Only projections acquired during a narrow phase window of the breathing cycle are used for reconstruction. This eliminates motion blur but reduces the effective number of projections by 80–90%, resulting in severe undersampling, pronounced streaking artifacts, and degraded soft-tissue contrast. Scan time and/or imaging dose must be increased to compensate. 3. Phase-sorted 4D-CBCT (Sonke et al., 2005) — Projections are binned into typically 8–10 motion phases using a respiratory surrogate signal (e.g., external fiducial marker), and each bin is reconstructed independently, yielding a time-resolved series of 3D volumes. This preserves the full acquired dataset but divides projections among bins, creating the same undersampling penalties as gating. Each of the above techniques has its own limitations and/or disadvantages, and there is a need for more efficient methods. Recent research has explored advanced algorithms, such as deformable image registration and machine learning-based approaches (Amirian et al., 2024), to improve motion estimation in medical imaging. This thesis will build upon these advancements to develop a novel motion compensation algorithm that can be integrated into our CBCT reconstruction pipeline. 3 Purpose and Aim of the Thesis The purpose of this thesis is to investigate and prototype motion compensation methods for CBCT imaging in radiation therapy. The aim is to develop a motion compensation algorithm that can effectively mitigate the effects of patient motion, particularly respiratory motion, while maintaining image quality, computational efficiency and minimizing the acquisition time and delivered dose to the patient. The thesis will involve a comprehensive literature review, algo[1]rithm development, and performance evaluation, with the goal of improving image quality and treatment accuracy in CBCT imaging for radiation therapy. 1. Research Question: How can we develop and implement a motion compensation al[1]gorithm for CBCT imaging that effectively mitigates the effects of patient motion, par[1]ticularly respiratory motion and still limit the acquisition time and delivered dose to the patient? 2. Objectives: (a) Conduct a comprehensive literature review on existing motion compensation techniques in CBCT imaging. (b) Develop, or adapt1, a motion compensation algorithm that can be integrated into the CBCT reconstruction pipeline. (c) Evaluate the performance of the developed algorithm in terms of image quality, computational efficiency, and robustness. (d) Compare the proposed algorithm with existing methods to assess its advantages and limitations. (e) Document the methodology, results, and conclusions in a comprehensive report, and provide the source code for the developed algorithm. 4 Output The expected output of this thesis will be a prototype implementation of a motion compensation algorithm that can be integrated into our CBCT-image reconstruction pipeline. The student will be responsible for developing and testing the algorithm, as well as evaluating its performance in terms of image quality and computational efficiency. The final deliverables will include a comprehensive report detailing the methodology, results, and conclusions, as well as the source code for the developed algorithm. 5 Who are we looking for? The ideal candidate for this thesis project should have a strong background in physics, medical imaging, and machine learning. Preferred qualifications include experience with programming languages such as Python and familiarity with image processing libraries and frameworks. The student should be motivated, detail-oriented, and capable of working independently as well as collaboratively in a research environment. The project includes a literature study, algorithm development, and performance evaluation, so the student should be comfortable with both theoretical and practical aspects of research. 6 Practicalities • Location: Elekta AB, Stockholm, Sweden • Supervisor: Niklas Gunnarsson (niklas.gunnarsson@elekta.com) • Start date: Spring 2027, exact date to be agreed upon. References Amirian, M., Barco, D., Herzig, I., & Schilling, F.-P. (2024). Artifact reduction in 3D and 4D cone-beam computed tomography images with deep learning: A review. IEEE Access, 12, 10281–10295. https://doi.org/10.1109/ACCESS.2024.3353195 Chen, G. T., Kung, J. H., & Beaudette, K. P. (2004). Artifacts in computed tomography scan[1]ning of moving objects. Seminars in Radiation Oncology, 14 (1), 19–26. https://doi.org/https://doi.org/10.1053/j.semradonc.2003.10.004 Kincaid Jr., R. E., Yorke, E. D., Goodman, K. A., Rimner, A., Wu, A. J., & Mageras, G. S. (2013). Investigation of gated cone-beam CT to reduce respiratory motion blurring. Medical Physics, 40 (4), 041717. https://doi.org/https://doi.org/10.1118/1.4795336 Sonke, J.-J., Zijp, L., Remeijer, P., & van Herk, M. (2005). Respiratory correlated cone beam CT. Medical Physics, 32 (4), 1176–1186. https://doi.org/https://doi.org/10.1118/1.1869074 About Elekta As a leader in precision radiation therapy, Elekta is committed to ensuring every patient has access to the best cancer care possible. We openly collaborate with customers to advance sustainable, outcome-driven and cost-efficient solutions to meet evolving patient needs, improve lives and bring hope to everyone dealing with cancer. To us, it's personal, and our global team of 4,700 employees combine passion, science, and imagination to profoundly change cancer care. We don’t just build technology, we build hope. Elekta is headquartered in Stockholm, Sweden, with offices in more than 120 countries and listed on Nasdaq Stockholm. For more information, visit elekta.com or follow us on LinkedIn, Glassdoor, Twitter, Facebook, Instagram and YouTube.