Bio Imaging and Signal Processing

Open rank position in machine learning for medical image and signal processing

Information about the position: This position is focused on research in applications of image and signal processing in the biomedical area, e.g. developing automatic methods to interpret images and signals from medical imaging systems and other biomedical sensor modalities. We aim to develop state-of-the-art meth- ods for medical image and signal processing, based on key enabling techniques from machine learning, estimation, optimization and mathematical modeling. The research will be performed in close collabo- ration with medical researchers from Sahlgrenska Academy at Gothenburg University and other medical institutions within Sweden and from the international scene.

Major responsibilities: The holder of the position will perform research and apply for research grants. The department is responsible for both a bachelor program and a master program in biomedical engineering and the holder of the position will contribute both with teaching and continuous development of the two education programs. Supervision of students on bachelor, master and doctoral level is included.

The department has several ongoing medical research collaborations, for instance, with the Swedish CAr- dioPulmonary bioImage Study (SCAPIS), MedTech West, Stroke Centre West and the Department of Ra- diology at Sahlgrenska Academy, University of Gothenburg. One major responsibility for the candidate is to strengthen these collaborations and to establish new medical research collaborations with researchers at Sahlgrenska Academy and other medical partners. The candidate will supervise and co-supervise doc- toral students in a cross disciplinary research school being established jointly by Chalmers and Sahlgrenska Academy at University of Gothenburg.

Position summary: Full-time permanent employment.

Qualifications: We are looking for a researcher with solid mathematical knowledge capable of performing research at the international forefront. As a candidate you should have experience in recent machine learn- ing methods applied to problems in the field of medicine. Mandatory is a PhD degree in signal processing, image analysis or in a similar subject area with a proven track-record of i) an independent and interna- tionally recognized line of research within the field and ii) good ability to supervise doctoral students iii) ability to teach in the undergraduate and graduate curriculum at the Department of Electrical Engineer- ing https://www.chalmers.se/sv/institutioner/e2/Var-Utbildning/Masterprogram iv) have published in major scientific journals within the field v) have presented your research at main international conferences, such as ICCV, ECCV, CVPR, NIPS, MICCAI, ICASSP and EMBC vi) ability to attract research funding from external funding agencies vii) ability to perform research with collaborators from the medical sciences.

For more information and how to apply see: hhttps://bit.ly/3fgKavv 

Application deadline: August 31, 2020.

A postdoctoral scholar position with a focus on applications of machine learning in cardiac MRI. Details can be found at:

https://recruit.ap.uci.edu/JPF05862

Job #JPF05862

• The Henry Samueli School of Engineering - Biomedical Engineering

Recruitment Period

Open date: November 19th, 2019 Next review date: Friday, Jan 3, 2020 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee. Final date: Friday, Feb 28, 2020 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

Description

The UCI Department of Biomedical Engineering (BME) in the Henry Samueli School of Engineering is recruiting a highly motivated and creative individual for a postdoctoral scholar position with a focus on applications of artificial intelligence in cardiac MRI. The projects at Kheradvar research Group (KLAB) are at the intersection of engineering, mathematical sciences, clinical cardiology, cardiothoracic surgery, and developmental biology. The candidate will be working on a joint project between Prof. Kheradvar and Prof. Jafarkhani (the UCI’s Center for Pervasive Communications and Computing (CPCC).

The desired candidates must have:
• Machine Learning & AI Experience
• Signal Processing/ Image Processing knowledge
• Understand Python architecture - must have a basic understanding of code primarily python.
• Experience working in a team as a dev or the team mind set in an Agile Environment
• Must understand AI algorithms so (coding & Math) at a level to DESIGN new algorithms
• Must be up to date with AI Architecture
• Plus: Experience in MRI
• Plus: Web developer experience

Requirements: Ph.D. in electrical engineering, biomedical engineering, computer science/engineering, physics, mathematics, statistics, or related fields. Ability to work well with a diverse group of scientists. Excellent oral and written communication skills.

The initial appointment for this position will be for 1 year with potential for renewal. Salary is commensurate with qualifications and years of experience. NIH scale will be used to determine salary, and a generous benefits package is provided per the university policies. Note: Total duration of an individual’s postdoctoral service may not exceed five years, including postdoctoral service at other institutions.

Application Procedure: Applicants will need to upload curriculum vitae, name/addresses of at least three references and cover letter expressing area(s) of interest to our online RECRUIT system at https://recruit.ap.uci.edu/apply/JPF05862

Screening will begin on January 3, 2020 and continue until position is filled.

The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence through diversity. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.

Job location

Irvine, CA

Learn More

More information about this recruitment: http://engineering.uci.edu/dept/bme Apply here: https://recruit.ap.uci.edu/JPF05862 Send an emial to Prof. Arash Kheradvar (arashkh@uci.edu) and/or Prof. Hamid Jafarkhani (hamidj@uci.edu) for further information.

Requirements

Document requirements

• Curriculum Vitae - Your most recently updated C.V.

• Cover Letter - Express areas of interest.
  (Optional)

• Misc / Additional (Optional)

Reference requirements

• 3 required (contact information only)

The aim of this postdoc project is to develop a novel ultrasound methodology that enables non-invasive read-out of the acoustic properties of radiation-sensitive microbubbles in order to construct a dose map. Hereto, acoustic models of wave propagation through soft tissue will be combined with advanced signal processing techniques. The developed methodology will extensively be validated in experimental setups (both in-vitro and in-vivo).

Background: Recent records on cancer incidence and mortality as well as on the associated economic burden, attest that cancer will remain a major and worldwide public health problem with serious socio-economic impact in the forthcoming decades. Comprised in the cure of approximately 50% of all cancer patients, radiation therapy is a fundamental pillar in their treatment. Relying on the tissue damaging properties of ionizing radiation, radiation therapy aims to maximally expose tumor tissue with minimal healthy tissue exposure. Thereto, recent advances in radiation therapy enable the planning and delivery of complex dose distributions exhibiting high tumor conformity. However, increased tumor conformity requires increased delivery accuracy which needs to be verified to ensure appropriate tumor exposure and minimal healthy tissue irradiation. This implies a growing need for appropriate treatment verification strategies effectively measuring the actual radiation dose imparted on the tumor. Despite this unmistakable need, current dosimetry technology is lagging behind on radiotherapy planning and delivery evolutions. As a consequence, radiotherapy cannot exploit its full capability.   About the co-supervising labs and the university: The main part of the research will be conducted at the Lab on Cardiovascular Imaging & Dynamics is part of the Department of Cardiovascular Sciences of the University of Leuven (www.kuleuven.be). It is embedded within the Medical Imaging Research Center (MIRC; https://mirc.uzleuven.be/MedicalImagingCenter), a multi-disciplinary research institute with approximately 100 researchers working on fundamental and translational research in the area of medical imaging and image processing. The MIRC is located on the campus of the university hospital Gasthuisberg (www.uzleuven.be) where researchers and clinicians work in close cooperation. The research is in collaboration with the Stadius Centre for Dynamical Systems, Signal Processing, and Data Analytics (STADIUS, http://www.esat.kuleuven.be/stadius) at the Electrical Engineering Department (ESAT) at KU Leuven. STADIUS's major research objective is to contribute to the development of improved digital control and signal processing systems that incorporate advanced mathematical modeling techniques as a crucial new ingredient. STADIUS draws concepts from mathematical fields such as linear and multi-linear algebra, statistics, discrete mathematics, optimization, etc.   Context: The postdoc project is part of a large research effort (called “Amphora”) at the European level on developing a new sensor system that enables measuring local radiation dose in-situ. Hereto, small microbubbles will be used as local sensors to radiation that can be read out using ultrasound waves. Please visit www.amphora-project.eu for more detailed information.

Profile:

• You have a PhD degree in (wave) physics, signal processing or biomedical engineering
• You have a solid mathematical background enabling to understand physical models
• You have a strong interest in wave physics and signal processing
• You are practical and can build experimental setups independently
• Being familiar with ultrasound imaging and its applications is an asset
• You have good programming skills in Matlab and/or in C/C++
• You are fluent in oral and written English
• You are enthusiastic and result oriented
• You can work independently with a critical mind set
• You have strong team-player skills
• You have NOT worked in Belgium in the past 3 years (this is a funding requirement)

Offer: We offer a postdoc position for 2 years with a market conform wage in a large, multidisciplinary research center in the heart of Europe, at a highly-ranked university. The position is immediately available and is co-supervised by experts in the field of ultrasound imaging and signal processing.

Interested?

For more information please contact Prof. dr. Jan D'hooge, tel.: +3216349012, mail: jan.dhooge@kuleuven.be or Prof. dr. ir. Alexander Bertrand, tel.: +32 16 32 18 99, mail: alexander.bertrand@kuleuven.be.   Apply through this website: https://www.kuleuven.be/personeel/jobsite/jobs/55466914 (website expires after Dec. 7th, after this date, please contact us directly at alexander.bertrand@esat.kuleuven.be and jan.dhooge@kuleuven.be and we could still consider your application)

The Department of Bioengineering (BIOE) at the University of Illinois at Urbana-Champaign (UIUC) invites applications for an open rank teaching faculty position in all areas of bioengineering.  We seek highly qualified applicants with a strong commitment to excellence in teaching and the ability to teach at all levels.  This is a 100% non-tenure-track, renewable appointment on an academic year (nine-month) service basis paid over twelve months.

The University of Illinois is an Equal Opportunity, Affirmative Action employer.  Minorities, women, veterans and individuals with disabilities are encouraged to apply. For more information, visit http://go.illinois.edu/EEO.  We have an active and successful dual-career partner placement program and a strong commitment to work-life balance and family-friendly programs for faculty and staff (http://provost.illinois.edu/faculty-affairs/work-life-balance/).

Applicants for this position must have a Ph.D. in bioengineering, medicine, or a related field.  Ideal candidates will have multiple years of experience in teaching core courses in a terminal degree program.  Previous experience in teaching courses in instrumentation and signals and systems in bioengineering is preferred.  Other areas of bioengineering relevant to the mission of the department will also be considered.  Competitive applicants will show the promise of excellence in classroom teaching and will demonstrate strong teaching knowledge.  Successful applicants will join the department’s thriving community of creative, passionate, and innovative teaching faculty who contribute to high-quality instruction, curriculum development, and student mentoring.  Many faculty also engage in outreach and service activities.  Ideal candidates include those who demonstrate evidence of a commitment to diversity, equity, and inclusion through research, teaching, and/or service endeavors.

BIOE at the UIUC is experiencing a period of programmatic growth, anticipating significant increases in course offerings and student numbers in both graduate and undergraduate programs.  With the completion of a new building and the launch of a new engineering-driven College of Medicine on the UIUC campus, the opportunities to influence engineering education are many. 

In order to ensure full consideration, applications must be received by October 21, 2019.  Applicants may be interviewed before the closing date; however, no hiring decision will be made until after that date.  Salary will be commensurate with qualifications.  Preferred starting date is as soon as possible, but is negotiable.  Applications should be submitted by visiting http://jobs.illinois.edu and uploading in one PDF file a cover letter, curriculum vitae, teaching statement, and names and contact information for three references.  Applicants may also submit supporting material relevant to evaluating their teaching abilities.  For inquiry, please email Amy Meharry at amym@illinois.edu.

The University of Illinois conducts criminal background checks on all job candidates upon acceptance of a contingent offer.

Position:

Research Assistant Professor position on MRI data analysis at Tulane

Organization:

Tulane University

Location:

New Orleans, USA

Description:

A Research Assistant Professor position is available immediately to work on the development of machine learning, image processing, statistical and signal processing approaches for the analysis and integration of genomic and MRI data.  More information about our research work at Multiscale Bioimaging and Bioinformatics Laboratory of Tulane Biomedical Engineering Department can be found at our website (http://www.tulane.edu/~wyp/).  The position will be funded by both NIH and NSF. The candidate will have a chance to collaborate with people at Tulane School of Sciences and Engineering, School of Public Health and Tropic Medicine and School of Medicine. Tulane is a private university and a member of the 63 prestigious Association of American Universities (AAU). Tulane is ranked as the 44th best national university in 2018 by US News Report, providing a unique environment for learning and research. The salary is commensurate with the experiences of the candidate.

Qualifications:

(1) A PhD degree in Applied and Computational Mathematics, Biomedical Engineering, Electrical Engineering, Computer Science, Statistics or other related fields; (2) Programming skills with MATLAB or C; (3) Experience and knowledge of signal processing, machine learning and statistical analysis; (4) Knowledge of biology and genomics is desirable but not required

To apply for the position, please send CV with a list of three references to wyp@tulane.edu

Several funded research opportunities are available in the Biomedical Image Computing Group at the University of New South Wales, Sydney, Australia. The group is based jointly in the School of Computer Science and Engineering and the Graduate School of Biomedical Engineering within the Faculty of Engineering. Research in the group focuses on the development of advanced computational methods for automated image analysis and downstream data analytics to improve the reliability and throughput of imaging based studies in medicine and biology. Applications include medical diagnostics, therapy planning and monitoring, population screening, and fundamental research in the health and life sciences. Strong collaborations exist with local and (inter)national hospitals, medical research centers, and strategic research consortia, providing challenging data and problems requiring powerful solutions.

Postdoc Position
A full-time postdoctoral research position is available in the area of deep learning for biomedical image analysis. The computational methods developed in the group are increasingly based on machine learning using deep artificial neural networks. To support ongoing research in the next 2-3 years and to explore fundamentally new approaches to deep learning, we seek to hire a (senior) researcher (Level A or B) with strong expertise in this area.

The selection criteria for this position include:

• PhD degree (or soon to be awarded) in biomedical image computing or related area.
• Strong expertise in machine learning and in particular deep neural networks.
• Demonstrated ability to conduct independent research with limited supervision.
• Demonstrated track record of relevant journal and conference publications.
• Demonstrated ability to work in a team and collaborate across disciplines.
• Ability (demonstrated if more senior) to supervise research students.

PhD Positions
Scholarships are available for top-class MSc or four-year honors BSc graduates seeking to undertake a research program at doctoral level leading to the PhD degree based on a solid thesis. Possible research topics include histopathological image analysis for fast and accurate cancer diagnosis, radiomics for imaging biomarker discovery in neurodegenerative and other diseases, neuronal cell and network image analysis to understand brain function, muscle tissue segmentation and deformation analysis to support longitudinal studies of muscular development, or related topics depending on own interests. All projects will involve the use of deep learning and other advanced artificial intelligence methods.

The selection criteria for these positions include:

• MSc or honors BSc degree in computer science or other relevant area.
• Experience with machine learning and in particular deep neural networks.
• Demonstrated affinity with biomedical image processing and analysis.
• Track record of relevant journal and conference publications.
• Ability to work in a team and collaborate across disciplines.

How to Apply
To express your interest in any of these positions, send the following information to Erik Meijering:

• Curriculum vitae listing your training, expertise, publications, awards, prizes.
• Transcripts of under/postgraduate certificates and lists of followed courses with grades.
• Letter of up to one page describing your motivation and personal research interests.
• List of at least two referees with their contact details.

The Brain Image Analysis Unit at the Center for Brain Science (CBS), RIKEN, Japan, seeks highly motivated individuals who will contribute to the development and implementation of image processing and image analysis techniques with a focus on brain image data.

The work will be done in a highly interdisciplinary research group consisting of scientists from the neural-scientific and medical research fields.  The Brain Image Analysis Unit integrates deep learning techniques into new algorithms to improve state-of-the-art processing and analysis of brain imaging data. Emphasis is placed on developing methods for image registration, image stitching, tracking of neurons and axon fiber bundles, detection, and segmentation of structures and denoising, enhancement, and visualization of images.

CBS website: https://cbs.riken.jp/en/faculty/bia/
Lab website: http://bia.riken.jp/

About the unit and the project

The Brain Image Analysis Unit develops new algorithms for the processing and analysis of multi-modal brain imaging data such as two-photon, bright-field microscopy images, and MRI.
We are in close collaboration with scientists from the neural-scientific and medical research fields. As a member of the Brain/MINDS project, the unit analyzes image data of the brain of the common marmoset monkey to help better understand the structure and function of the primate brain.

Artificial intelligence plays an important role in contemporary image analysis. In particular, machine learning techniques such as deep learning are indispensable for the automated analysis of large image data-sets. The Brain Image Analysis Unit contributes to this exciting new field by integrating deep learning techniques into new algorithms to improve state-of-the-art processing and analysis of brain imaging data. Emphasis is placed on developing methods for image registration, image stitching, tracking of neurons and axon fiber bundles, detection, and segmentation of structures and denoising, enhancement, and visualization of images.

Job description

The selected candidate will join the interdisciplinary Brain/MINDS project, and as a member of the unit will contribute to the development and implementation of image processing and image analysis techniques with a focus on (marmoset) brain image data. 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. 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 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 experience in developing algorithms for the analysis/processing of biological/medical/neural images, computer vision, machine learning, deep learning, optimization, simulation, or similar fields, demonstrated by high-quality publications
good English communication skills 
proficiency in a programming language (such as C++/Python/JS)
good communication skills and ability to cooperate

Application & Employment

Start: October, 2019 (negotiable). A renewable one-year fixed-term employment contract to a maximum of the end of fiscal year 2023 (March 31, 2024), with annual evaluation. For further details, please refer to the job posting URL
https://cbs.riken.jp/en/careers/20190530_w19047_bia_r.html

 

As part of the new project Ecce Aqua one fully funded PhD fellowship is available at the University of Padova (Italy) on imaging and big data analytics applied to marine vertebrates (http://www.dottorato.veterinaria.unipd.it/health-aquatic-animals).
We welcome candidates with background in some of the following fields: image analysis, computational microscopy, machine/deep learning, data science and statistics, radiomics.

Closing date: 14-05-2019 13:00

Supervisors and contacts
Enrico Grisan, Department of Information Engineering, enrico.grisan@unipd.it
Livio Corain, Department of Management and Engineering, livio.corain@unipd.it
Bruno Cozzi, Department of Comparative Biomedicine and Food Science, bruno.cozzi@unipd.it

Short description
The overall aim of the project is to develop processing pipelines for the analysis of CT and MRI scans from marine fauna (cetaceans, turtles, fishes) with a specific emphasis on the study cetacean brain. Additional ex-vivo histological data will be available to provide an integrated digital imaging approach to comparative anatomy. The PhD student will be part of a highly multidisciplinary teams composed by computer scientists, engineers, statisticians, biologists and neuroanatomists.

The PhD program is designed as a strongly interdisciplinary research environment that is made up of three overlapping layers: comparative anatomy, imaging and data science for big data analytics. The comparative anatomy of marine mammals represents the main layer at the crossroads between imaging and data analysitics. Imaging and data science play a synergic role in handling big data under multi-faceted circumstances and goals, focusing on 3D/2D reconstruction and interpretation of imaging information. Data science aims at developing innovative inference-based methods to investigate possible (small) effects due to factors such as species, sexual dimorphism, aging and pathology.

The topics that can define the doctoral project are:
Imaging:
o        3D shape reconstruction and registration of multimodal data
o        2D to 3D image registration and visualization
o        Artificial intelligence for the segmentation and classification of histological images
Big Data Analytics:
o        Web-based apps development and set-up of a tissue digital database
o        Multivariate testing and ranking methods
o        Parallel programming for efficient randomization algorithms

Application procedure
Candidates must apply online at https://pica.cineca.it/unipd/dottorati35
selecting the PhD position labelled as: Progetto "ECCE AQUA" - Topic: Tissues images analyses by using big data management and evaluation;

Instructions - Help
 

Apply here: https://www.kuleuven.be/personeel/jobsite/jobs/55004357?hl=en&lang=en

Project: 

This job opening covers a research position at the STADIUS group of the Department of Electrical Engineering (ESAT) of KU Leuven (Belgium) for a Ph.D. candidate in the frame of an ERC project on signal processing algorithm design for next-generation wearable neuro-technology and neuro-sensornetworks.  A specific focus is on the design of adaptive multi-channel neural signal processing algorithms, amenable to low-power distributed or parallellizable architectures with constrained energy resources.

Profile

Candidates must hold a Masters degree in Electrical or Computer Science Engineering (or equivalent) with excellent grades, and with a strong mathematically-oriented engineering background. A good knowledge in the following fields is deemed necessary:

-Signals and systems

-Linear algebra

-Signal processing 

-Analysis of random/stochastic signals (stationarity, power spectral density, estimation theory, Wiener, etc.) 

Additional research/educational experience in any of the following topics is a plus:

- Multi-channel signal processing and spatial filtering

- (Blind) source separation

- Sensor array processing (beamforming, detection, …)

- (Convex) optimization theory 

- Brain-computer interfaces and neural decoding

- Component analysis theory and application (PCA, ICA, IVA, CCA, …)

- Machine learning (deep or not)

Candidates should be motivated, independent, critical, and should have strong team-player skills. Excellent proficiency in the English language is also required, as well as good communication skills, both oral and written.

Offer

- An exciting interdisciplinary research environment at KU Leuven, Europe’s most innovative university (Reuters: https://www.reuters.com/innovative-universities-europe-2018/profile?uid=1 ) - A Ph.D. title from a high-ranked university (after +- 4 years of successful research) - A thorough scientific research-oriented education - The possibility to become a world-class researcher - The possibility to participate in international conferences and collaborations - A competitive monthly stipend (scholarship)   More info: https://www.kuleuven.be/personeel/jobsite/jobs/55004357?hl=en&lang=en