Bio Imaging and Signal Processing

Postdoctoral Fellow, Research Scientist, and Instructor in Biomedical Optics and Medical Physics

We are looking for skilled and enthusiastic candidates to fill Postdoctoral Fellow, Research Scientist, and Instructor positions in the Biomedical Imaging and Radiation Technology Laboratory(BIRTLab) at Department of Radiation Oncology in UT Southwestern Medical Center. Our mission is to innovate, develop, and apply biomedical technology to empower cancer research.

Successful candidates will be joining our team to work either one of the following projects:

(1). Establishing an ultra-sensitive optical imaging integrated with X-ray cone beam CT(CBCT)/MRI imaging for in vivo tumor and immune cell tracking to facilitate cancer therapy development. The research involves imaging reconstruction, and the development of camera-lens imaging system or single pixel imaging.

(2). Developing optical tomography-guided system for pre-clinical radiation therapy research; specifically, we will develop a fluorescence, bioluminescence, and diffuse optical tomography system to localize tumors in vivo, guide irradiation, and quantify treatment response.

(3). Establishing molecular image-guided system for ultra-high-dose rate (FLASH) radiation therapy as a new cancer treatment paradigm; the research involves numerical oxygen transport modeling, Monte-Carlo simulation, optical imaging and radiation physics to assess the efficacy of FLASH therapy.

The projects are multi-disciplinary and integrate engineering, algorithm development, optics, radiation physics, biology, and industrial components. Success completion of the projects will significantly advance image-guided systems and radiation technology to improve cancer treatment.

BIRTLab provides an outstanding environment to grow candidates toward successful careers.

• PI Dr. Wang works tirelessly with candidates to ensure they meet their career goals. Through attentive guidance, he encourages members to think creatively and develop their own research projects. All activities are supported by extramural funding through the NIH and Texas CPRIT.
• Successful members are also eligible for basic clinical medical physics training and a tuition fee waiver to enroll in a certificate program with CAMPEP-accredited courses, which covers medical physics didactic elements for people who enter the medical physics profession through an alternative pathway.

Multi-disciplinary projects, a strong research environment, and the medical physics pathway together provide a unique opportunity to prepare the candidate for careers in academia and industry, or to become a professional medical physicist in the U.S.

Candidates with established experience in numerical algorithm development, biomedical optics, or engineering system design and development are desired. Candidates who hold degrees in mathematics, physics, biomedical engineering, optics, computer science and engineering are encouraged to apply. Further details about the BIRTLab and projects can be found at https://www.utsouthwestern.edu/labs/birt/

Position and compensation are based on candidates’ experience and NIH scale with highly competitive benefits. UT Southwestern Medical Center is in Dallas, Texas. Dallas is the fourth-largest metropolitan area in the US with fast growing industrial sectors and job opportunities. Interested candidates should send a statement of interest, CV, and the contact of 3 references to:

Ken Kang-Hsin Wang, Ph.D., DABR

Associate Professor

CPRIT Scholar in Cancer Research

Division of Medical Physics and Engineering

Department of Radiation Oncology

UT Southwestern Medical Center

Kang-Hsin.Wang@utsouthwestern.edu

Positions: The Gordon Center for Medical Imaging (GCMI) in the Department of Radiology at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) has multiple openings for highly qualified individuals at the postdoctoral level to work with Prof. Kuang Gong on NIH funded projects related to PET image reconstruction, medical image analysis, and machine learning methodologies.

The research projects aim to utilize machine learning-based image reconstruction and analysis to improve the diagnosis and progression tracking of Alzheimer’s disease (AD) and cancer. The projects are based on collaborations with clinicians from MGH, Harvard Aging Brain Study (HABS) and MD Anderson Cancer Center (MDACC). The successful candidate will have joint appointments at MGH and HMS.

Requirements:

·      Applicants should have earned a Ph.D. in engineering, statistics, mathematics, physics, neuroscience, or a related field.

·      Strong analytical, quantitative, programming and communication skills are essential.

·      Prior research experience with image reconstruction or medical image analysis is required.

·      Prior research experience with machine learning or deep learning, and proficiency in Pytorch/TensorFlow programming is desirable.

·      Applicants should be self-motivated and able to work independently as well as in a collaborative environment.

Environment: The Department of Radiology offers extensive core research facilities, including a new digital time-of-flight PET/CT scanner, brain and whole-body PET/MRI scanners, small animal PET/SPECT/CT systems and several MRI scanners, including two 7T ultra-high-field scanners. It also includes a large-scale computing facility for image analysis, network training, tomographic reconstruction, Monte Carlo simulation, and other computationally intensive research applications. The successful applicant can interact collaboratively with a large, growing research group in diverse areas of imaging technology and applications.

Apply: The positions are available as of June 2022 and the start date is flexible. If interested, please send your curriculum vitae, a cover letter describing your background and research interests, and contact information of three references to Prof. Gong (kgong@mgh.harvard.edu). Applications will be reviewed in a rolling basis until the positions are filled.

Machine learning and specifically deep learning techniques are promising tools in medical image analysis and they have demonstrated very good performances in many tasks, such as image segmentation. These techniques are though data demanding and as such they need large-scale cohorts, often multi-centric datasets. In this context, Domain Adaptation (DA) has recently raised strong interests in the medical imaging community as the generalization of algorithms to unseen data (domain shift), different input data domains (missing modalities) and the uncertainty of the networks output due to domain shift are still open problems. Nevertheless, all these aspects are crucial in order to translate AI models for medical image analysis methods to be evaluated in large-scale heterogenous imaging acquired in clinical practice.

In this context, we are looking for a full-time post-doctoral researcher to join the CIBM Signal Processing CHUV-UNIL section. The researcher will focus on domain adaptation, federated learning and other generalization solutions for AI-based reconstruction, segmentation and classification for Magnetic Resonance Imaging (MRI) analysis. This position aims also to investigate different aspects of explainable AI linked to domain shifts. The research will be conducted in the context of AI segmentation and classification models for assessment of advanced imaging biomarkers in Multiple Sclerosis.

Your profile

• A PhD degree in engineering, electrical engineering, computer science, physics or related fields

• Strong background in image processing and deep learning techniques is a must, with published papers in key journals (TMI, MedIA, etc) and conferences in the field (MICCAI, MIDL, NEURIPS, CVPR, etc).

• Demonstrated previous experience in different aspects of domain adaptation in reconstruction/segmentation or classification problems is required.

• Experience in neuroimage analysis is a plus.

• You certify proficiency in programming (Python, PyTorch/Keras, Javascript, bash, etc)

• You are eager to supervise and transfer your knowledge to master and PhD students and promoting a collaborative environment within CIBM sections.

• You have excellent written and oral communication skills in English; French is a plus.

• Rigorous work habits, a curious and critical mind, and a good sense of initiative.

• A high-level perseverance and a strong personal commitment are expected.

How to apply

Please send your CV, two references and a motivation letter to Dr. Meritxell Bach Cuadra (meritxell.bachcuadra@unil.ch).

Open call can be downloaded here.

The Department of Electrical Engineering at Stanford University (http://ee.stanford.edu/) invites applications for a tenure-track faculty appointment at the junior level (Assistant or untenured Associate Professor) in the broadly defined field of electrical and computer engineering. Priority will be given to the overall originality and promise of the candidate’s work over any specific area of specialization.

Applicants should have an earned Ph.D., evidence of the ability to pursue an independent program of research, a strong commitment to both graduate and undergraduate teaching, and the ability to initiate and conduct research across disciplines. A successful candidate will be expected to teach courses at the graduate and undergraduate levels and to build and lead a team of graduate students in Ph.D. research.

Applications should include a brief research and teaching plan, a detailed resume including a publications list, and the names and email addresses of at least five references.

The Electrical Engineering Department, School of Engineering, and Stanford University value faculty who are committed to advancing diversity, equity, and inclusion. Candidates may optionally include as part of their research or teaching statement a brief discussion of how their work will further these ideals.

Candidates should apply online at http://ee.stanford.edu/job-openings. Applications will be accepted through November 28, 2021.

Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University's research, teaching and clinical missions.

Inviting applications for a rolling Ph.D. admission at Indraprastha Institute of Information Technology-Delhi (IIIT-D) on project areas in biomedical signal and image processing including cancer imaging, cancer genomics, and EEG/ECG signal processing.

No. of openings: Two

Monthly Remunerations: Rs. 31,000/- (+HRA will be provided if you are not residing on the IIITD campus)

Essential Qualifications

• B.Tech/M.Tech in ECE/CSE with outstanding academic records
• Good communication skills.
• Proficient in MATLAB and/or Python

Desired Qualifications

• UGC/CSIR JRF(Net) qualified
• Competence in machine learning/deep learning

Application Deadline: The positions will be filled as soon as suitable candidates are found.

Application Process: Send your CV via email to anubha@iiitd.ac.in . Please mention “Rolling PhD admission” in the subject line of your email.

Selected candidates will be a part of the Signal Processing and Biomedical Imaging Lab (SBILab), IIIT-D. We have many national and international collaborations. Please visit the website of SBILab for the research work being undertaken in our lab at http://sbilab.iiitd.edu.in/.

Job offer: Post-doc in biomedical image analysis

We are seeking candidates who are interested in developing deep learning algorithms for improving the registration/alignment of our 2D/3D MRI and microscopy images. 

Job description

The selected candidate will join the interdisciplinary Brain/MINDS project which aims at studying the neural networks controlling higher brain functions in the marmoset, to gain new insights into information processing and diseases of the human brain.

As a member of the project, the selected candidate will contribute to the development and implementation of image processing and image analysis techniques with a focus on brain image data, specifically marmosets. We are seeking candidates who enjoy developing deep learning algorithms for 2D/3D image registration / alignment.

The work will be done in a highly interdisciplinary research group consisting of scientists from the neural-scientific and medical research fields. The emphasis is on developing cutting-edge technologies that improve current state-of-the-art and publishing high impact work in top-tier journals in order to build a substantial resume and strong international collaborations.

Experiences in biomedical image analysis is an advantage but not a requirement. This job may be a great opportunity to apply knowledge and expertise from the computer vision and/or image processing field to new problems in the biomedical field.

Location

Wako-City (Kanto district, 2-1 Hirosawa, Wako, Saitama 351-0198). RIKEN is located in very close proximity to the northern part of Tokyo. Map: http://www.riken.jp/en/access/wako-map/.

The RIKEN campus is quite large and offers cafeterias, coffee shops, and a convenient store. From the nearest train station, it is only a 12 min train ride to the Ikebukuro-Station (Tokyo). The Ikebukuro-Station is a hub which connects many famous places in Tokyo, including Shinjuku (9 min train ride), Shibuya (18 min train ride) or Akihabara (19 min train ride). Many people prefer to avoid crowded streets and trains in their daily life and are living in close proximity to RIKEN. However, those who prefer living close to the sightseeing, nightlife and entertainment spots in Tokyo benefit from commuting out of the city in the morning, and returning in the evening (significantly less crowded than the other way around).

Qualifications

The candidate should have or be expecting to receive a Ph.D., by the time of employment, in related fields and have

• relevant research skills and experiences in developing deep learning techniques for the analysis/processing of images, demonstrated by high-quality publications.

• expertise in biological/medical/neural image processing, image registration, computer vision, machine learning, optimization, or similar fields, is an advantage.

• good English communication skills

• proficiency in a programming language (such as C++/Python/JS)

• proficiency in tensorflow, pytorch or a similar DL library

• good communication skills and ability to cooperate

Application & Employment

RIKEN employees enjoy the benefits of a generous vacation and leave package. An overview of benefits can be found here: working-at-riken. For application details, please refer to the official job posting URL: https://cbs.riken.jp/en/careers/20210226_w20294_h.skibbe_r.html.

Closing date: open until the positions are filled.

The Gordon Center for Medical Imaging (GCMI) in the Department of Radiology at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) in Boston, MA has an immediate opening at the postdoctoral level to work on research projects related to PET and MR image analysis, image restoration and image reconstruction.

The projects are funded by NIH, aiming to utilize machine learning-based image analysis to improve the diagnosis and progression tracking for Alzheimer’s disease (AD) and Neuroendocrine tumor (NET). The projects are based on cooperation with Harvard Aging Brain Study (HABS) and MD Anderson Cancer Center (MDACC).

Qualifications:

Applicants should have earned a Ph.D. in engineering, statistics/mathematics, physics, neuroscience, or a related field. Strong analytical, quantitative and programming skills as well as proficiency in machine learning are essential. Prior experience with PET/MR image analysis is not required. The successful candidate will have joint appointments at MGH and HMS.

Environment:

The Department of Radiology offers extensive core research facilities, including a new digital time-of-flight PET/CT scanner, brain and whole body PET/MRI scanners, and small animal PET/SPECT/CT systems. Studies on these imaging systems are supported by the MGH Gordon PET Core’s fully equipped blood/radiometabolite processing laboratory, on-site cyclotron, dedicated research radiochemistry laboratories, and a world class GMP radiopharmacy. The Gordon Center maintains a large-scale computing facility for image analysis, network training, tomographic reconstruction, Monte Carlo simulation, and other computationally intensive research applications. The successful applicant can interact collaboratively with a large (140+), growing research group in diverse areas of imaging technology and applications.

The position is available as of February 2021 and the start date is flexible. If interested, please send your curriculum vitae, a cover letter describing your background and research interests, and contact information of three references to Dr. Kuang Gong (kgong AT mgh.harvard.edu).

OPTIMA group (https://optima.meduniwien.ac.at) is seeking an exceptionally motivated postdoc to strengthen our interdisciplinary team working on deep learning for medical image analysis. As part of our new initiative on Artificial Intelligence in Retina you will be leading exciting projects, at the interface of computer science and medicine. The focus of the research is on automated characterization of retinal pathology from 3D optical coherence tomography (OCT) images of human eye, and on learning to predict patient-specific disease progression from very large-scale curated imaging data and electronic health records. The goal is to build an effective AI-based clinical decision support for retinal specialist, in a close collaboration with a leading OCT device company.

The successful candidate will be immersed into an interdisciplinary environment working closely with a team of computer scientists, software engineers and medical doctors. Advancements will have a real-world impact on clinical management of patients suffering from retinal diseases, a leading cause of blindness today.

Your profile

• PhD degree (or soon to be completed) in a relevant discipline.
• Strong publication record in relevant and refereed journals
• Strong background in machine and deep learning (PyTorch, TensorFlow, …)
• Excellent programming skills (Python, Julia, C/C++, …)
• Ability to organize his/her work with minimal supervision and to meet deadlines of the project.
• Excellent analytical, interpersonal, as well as written and oral communication skills in English

How to apply

Applicants with an excellent academic record, interested in machine learning for healthcare should send an email with their CV and a cover letter indicating their interests and research experience, and/or any inquiries to Hrvoje Bogunović (hrvoje.bogunovic@meduniwien.ac.at).

Female candidates are explicitly encouraged to apply!

Salary is prescribed by the university wage agreement, and it is €56k/year (brutto).

Environment

OPTIMA is an interdisciplinary research lab composed of retinal specialists, computer scientists and software engineers, developing innovative image analysis methods for personalized medicine in retinal disease. Our research focus lies on the quantitative analysis of state-of-the-art ophthalmic imaging data, in particular OCT, and the development of prognostic disease models for improved patient management in leading eye diseases. The lab has access to extremely large sets of ophthalmic images and is well-equipped with a dedicated high-performance computing cluster containing the latest generation GPUs. The group keeps close collaboration with several world-class academic research institutions, as well as partnerships with imaging device and pharmaceutical companies.

Postdoc and Associate Research Scientist Positions in Cardiac MRI

School of Biomedical Engineering

Shanghai Jiao Tong University

Description: Two positions--Postdoctoral Associate and Associate Research Scientist (faculty position)--are available at the Cardiac MRI Lab of Shanghai Jiao Tong University (SJTU). The long-term goal of the lab is to improve performance of MRI by improving scan efficiency, motion robustness, contrast mechanism, and data analysis. The responsibilities of these positions include development of novel pulse sequence and reconstruction algorithms for fast, automated, and motion-robust imaging of the heart, and development of machine learning methods for reconstruction and post processing. 

Research Environment: The Cardiac MRI Lab is part of the Institute of Medical Imaging Technology and School of Biomedical Engineering at SJTU. The center currently hosts a research-dedicated United Imaging uMR790 3T scanner. The lab has a strong collaboration with the vendor, United Imaging Healthcare, and clinicians (cardiologists/radiologists) at several Shanghai-based major hospitals that routinely practice CMR. The successful candidate will work in a passionate, multi-discipline, and productive research team.

Qualifications: The candidate should have or nearly have a PhD degree in following disciplines, including (not limited to) Electrical/Biomedical Engineering, Physics, Applied Mathematics, and Computer Science. Candidates who feel passionate about research and who have the following training experience are strongly encouraged to apply: 1) image reconstruction; 2) machine learning; 3) MR physics and pulse sequence development.

Application: Both positions are available for application from 2020/11/18-2021/02/28. To apply, please send your CV to Dr. Chenxi Hu (chenxi.hu@sjtu.edu.cn)  

Chenxi Hu, PhD

Tenure-Track Associate Professor

Department of Biomedical Engineering, Shanghai Jiao Tong University

http://bme.sjtu.edu.cn/En/FacultyDetail/336 (English);

http://bme.sjtu.edu.cn/Web/FacultyDetail/336 (Chinese)

Signal Processing and Algorithm Engineer

Are you a signal processing and algorithm engineer or data scientist with a broad skillset who loves to create, face difficult problems head on, and has a desire to always learn?

Job Overview

We are looking for an experienced signal processing specialist who can create and improve upon unique algorithms for use with a unique cardiovascular monitoring system. Algorithms include automated signal quality assessment, feature identification, clinical parameter estimation such as blood pressure, and more. Your primary goal will be to help us move fast while innovating and developing code that is well documented, highly modular and abstracted, while meeting FDA regulatory requirements. You must be a clear communicator, able to work independently, thrive in a startup environment, and be open to taking on new responsibilities. This position is based in Rochester, NY.

Key Responsibilities

• Algorithm development and optimization
• Data exploration
• Push the boundaries for what our products are capable of doing

Required Skills and Experience

• Signal processing
• Algorithmic thinking
• Continuous and discrete linear systems
• Python
• Mathematical modeling and optimization

Desired Skills and Experience

• Electrical engineering
• Data Science background
• Adaptive signal processing
• Biomedical signal processing
• Anatomy and physiology
• Pattern recognition
• Wide portfolio of personal projects spanning multiple disciplines

Heart Health Intelligence (HHI) will significantly reduce the cost of heart failure by preventing hospital readmissions through a toilet seat-based cardiovascular monitoring system and a mid-level provider run monitoring service. HHI will transform the healthcare system by enabling the transition from reactive to proactive care.

HHI provides competitive salaries and benefits and is an Equal Employment Opportunity Employer.

Email your resume to: hr@hearthealthintelligence.com.  No recruiters please.