Open Positions

Project goal is to develop a robotically-assisted photoacoustic endomicroscope to perform image-guided surgery of tumor margins during intra-operative surgery.

Post-doctoral research opportunities are available in the Wang Lab at the University of Michigan to join a highly collaborative, multi-disciplinary team to develop an end-to-end solution for an intra-operative photoacoustic imaging system to detect cancer.  A multi-modal confocal photoacoustic endomicroscope will be developed to detect next generation contrast agents specific for cancer targets.  The imaging prototype will be verified first in pre-clinical models and then in human subjects.  Clinical studies will be performed by a highly experienced international team of surgeons in collaboration with a global leader in robotic-assisted minimally invasive surgery.  The integrated solution will improve precision for tumor localization and differentiation from normal tissues to improve patient outcomes.  The successful applicant will have an opportunity to design a multi-element acoustic sensor array to generate 3D volumetric images with a large field-of-view.  A tunable OPO laser will be used to generate deep tissue penetration with near-infrared excitation.  A multi-channel analog-to-digital converter will be developed to acquire the photoacoustic signal, and a field-programmable gate array module will be incorporated to achieve greater image acquisition speeds.

Requirements: Candidates with a Ph.D. in engineering (mechanical/electrical/biomedical), optics, physics, or a related discipline with hands-on experience in instrumentation, data acquisition, control, optical design, or fiber optic systems are invited to apply.  Programming experience with Labview, Matlab, C++, and Solid Works is desirable.  International investigators are welcome.  Relevant skills include the following:

·   Proficiency in optical design and ray trace simulations

·   Hands-on experience with OPO lasers.

·   Experience in mechanical design, system assembly, prototyping, machining, and 3D printing.

·   Familiarity with the latest tools and equipment used in micro precision work.

·   Expertise in data acquisition and control of electro- and/or opto-mechanical components.

·   Proficiency in programming languages such as MATLAB, SolidWorks, and/or LabVIEW.

·   Excellent organizational and communication skills.

Project goal is to develop of state-of-the-art methods that combine imaging with biomarkers to demonstrate a targeted in vivo imaging strategy for early detection of colorectal cancer (CRC) that arises from either the traditional or serrated pathways.

Post-doctoral research opportunities are available in the Wang Lab at the University of Michigan to join a highly collaborative, multi-disciplinary team to accelerate clinical translation of a targeted near-infrared contrast agent for in vivo imaging of early CRC.  Target identification will be performed using scRNAseq analysis with trajectory inference on an existing patient database.  The biochemical structure of a peptide heterodimer that combines unique monomer sequences specific for cell surface targets overexpressed by colonic adenomas that arise from either the traditional or serrated pathway will be optimized.  The dimensions of PEG and amino hexanoic acid linkers will be tuned to prevent steric hindrance from peptide binding interactions with the IRDye800cw fluorophore.  Heterodimer binding interactions, including specificity, kinetics, and contrast, will be validated in vivo in a pre-clinical model of CRC using a prototype endoscope accessory.  Imaging will be performed using orthotopically implanted patient-derived adenoma organoids.  The validated peptide heterodimer will be clinically translated in the Medical Procedures Unit at Michigan Medicine to detect flat adenomas that account for many cases of CRC and would otherwise be missed.

Requirements:  Candidates with a Ph.D. in biochemistry, protein chemistry, medicinal chemistry, organic chemistry, physical chemistry, molecular biology, cell biology, structural biology, or a related discipline with hands-on experience in wet lab chemistry, peptide synthesis, and organ culture are invited to apply. Hands-on experience with small animal imaging is desirable.  International investigators are welcome.  Research skills to be mastered in this project include the following:

·       Identify promising tissue targets using scRNAseq analysis with trajectory inference

·       Select peptide monomers using phage display

·       Arrange peptide monomers in heterodimer configuration

·       Analyze peptide binding interactions using structural models

·       Optimize linker dimensions and configurations

·       Develop patient-derived organoids

·       Characterize peptide pharmacokinetics and biodistribution.

·       Assess peptide stability in serum.

·       Perform in vivo imaging in small animals.

·       Develop scientific independence, organizational, and communication skills.

Project goal is to develop of state-of-the-art methods that combine imaging with biomarkers to develop a targeted in vivo imaging strategy for early detection of esophageal cancer.

Post-doctoral research opportunities are available in the Wang Lab at the University of Michigan to join a highly collaborative, multi-disciplinary team to accelerate clinical translation of an integrated imaging strategy for early detection of esophageal adenocarcinoma in patients with Barrett’s esophagus undergoing surveillance endoscopy.  Target identification will be performed using single cell RNA sequencing and spatial transcriptomics analysis of human specimens from an existing clinical database.  Peptide monomers that bind specifically to tissue targets expressed uniquely by high-grade dysplasia will be identified using phage display methods.  The candidate monomer sequences will be optimized with structural models using Hex docking software.  Optimized monomers will be combined in a multimer configuration and labeled with a near-infrared fluorophore for fluorescence detection.  The dimensions of PEG and amino hexanoic acid linkers will be tuned to prevent steric hindrance from peptide binding interactions.  Binding interactions, including specificity, kinetics, and contrast, will be validated using a flexible fiber endoscopic imaging accessory.  In vivo imaging will be performed in pre-clinical models using implanted patient-derived organoids.  The validated peptide multimer will be clinically translated in the Medical Procedures Unit at Michigan Medicine to detect pre-malignant lesions that have potential to transform into adenocarcinoma and would otherwise be missed.

Requirements:  Candidates with a Ph.D. in biochemistry, protein chemistry, medicinal chemistry, organic chemistry, physical chemistry, molecular biology, cell biology, structural biology, or a related discipline with hands-on experience in wet lab chemistry, peptide synthesis, and organ culture are invited to apply.  Hands-on experience with small animal imaging is desirable.  International investigators are welcome.  Research skills to be mastered in this project include the following:

·   Identify promising tissue targets using scRNAseq analysis and spatial transcriptomics

·   Select peptide monomers using phage display methods

·   Arrange peptide monomers in multimer configuration

·   Analyze peptide binding interactions using structural models

·   Optimize linker dimensions and configurations

·   Develop patient-derived organoids

·   Characterize peptide multimer pharmacokinetics and biodistribution.

·   Assess peptide multimer stability in serum.

·   Perform in vivo imaging in small animal models.

·   Develop scientific independence, organizational, and communication skills.

Project goal is to modify the surface of ultrasmall superparamagnetic iron oxide nanoparticles with peptide ligands highly specific for liver cancer for use as a targeted MRI contrast agent.

Post-doctoral research opportunities are available in the Wang Lab at the University of Michigan to join a highly collaborative, multi-disciplinary team to accelerate clinical translation of a nanotechnology-based diagnostic MR imaging agent.  The surface of ultrasmall superparamagnetic iron oxide nanoparticles will be modified with a panel of peptide ligands to form a targeted multimer nanoprobe to distinguish indeterminant liver nodules.  Single cell RNAseq analysis will be performed to identify cancer specific tissue targets to improve detection performance.  Lead monomer peptides will be selected using phage display methods, and optimized using structural models.  The nanoparticle surface will be modified with a panel of cancer specific peptides.  The optimal peptide density will be identified, and MR relaxivity will be maximized.  The nanoprobe properties will be characterized, and cytotoxicity will be assessed.  Specific nanoprobes uptake by tumor, biodistribution, and clearance will be evaluated in vivo in a small and large animal pre-clinical model using MR imaging.

Requirements:  Candidates with a Ph.D. in biochemistry, chemistry, nanotechnology, molecular biology, cell biology, structural biology, or a related discipline with hands-on experience in small animal imaging and pre-clinical models are invited to apply.  Hands-on experience with small animal surgery is desirable.  International investigators are welcome.  Skills to be mastered in this project include the following:

·   Perform image-guided surgery in small animals.

·   Identify tumors using ultrasound imaging.

·   Detect tumors using MR imaging.

·   Characterize nanoprobe pharmacokinetics.

·   Characterize nanoprobe biodistribution.

·   Use brightfield and confocal microscopes.

·   Apply immunohistochemistry and immunofluorescence.

·   Self-motivated with excellent organizational and communication skills.

Project goal is to develop machine learning algorithms for a robotically-assisted imaging platform to enhance visualization of tumor margins during intra-operative surgery.

Post-doctoral research opportunities are available in the Wang Lab at the University of Michigan to join a highly collaborative, multi-disciplinary team to develop an end-to-end solution for a multi-modal imaging system to visualize tumor margins during intra-operative surgery.  A confocal photoacoustic endomicroscope will be developed to detect next generation contrast agents for cancer specific targets.  The imaging system will be verified first in pre-clinical models followed by in human subjects.  Clinical studies will be performed by a highly experienced international team of surgeons in collaboration with a global leader in robotic-assisted minimally invasive surgery.  The integrated solution will improve precision for tumor localization and differentiation from normal tissues to improve patient outcomes.  The successful applicant will have an opportunity to develop machine learning algorithms for real time clinical interpretation of in vivo fluorescence and photoacoustic images.  A portable platform will be used for fast processing speeds that will enable rapid clinical decision making in the operating room.  Training of deep learning models will be performed using datasets of images collected in vivo from human subjects.

Requirements: Candidates with a Ph.D. in computer science, engineering (e.g. electrical, biomedical, mechanical, aeronautics, etc), bioinformatics, statistics, or a related discipline with project experience in machine learning, deep learning, and natural language processing are invited to apply.  Programming experience with MATLAB, Python, and C++ is desirable.  International investigators are welcome.  Relevant skills include the following:

·   Expertise in relevant software programming languages

·   Experience with UNet architecture with MobileNet V2 backbone

·   Understanding of ResNet, Inception, and Xception.

·   Familiarity with Classification and Regression Tree (CART) and Random Forest (RF) methods

·   Proficiency in image denoising, motion artifact mitigation, and feature segmentation.

·   Knowledge of robotics systems, control systems, and systems engineering.

·   Excellent organizational and communication skills.

Project goal is to develop machine learning algorithms for a robotically-assisted imaging platform to enhance visualization of tumor margins during intra-operative surgery.

Post-doctoral research opportunities are available in the Wang Lab at the University of Michigan to join a highly collaborative, multi-disciplinary team to develop an end-to-end solution for a multi-modal imaging system to visualize tumor margins during intra-operative surgery.  A confocal photoacoustic endomicroscope will be developed to detect next generation contrast agents for cancer specific targets.  The imaging system will be verified first in pre-clinical models followed by in human subjects.  Clinical studies will be performed by a highly experienced international team of surgeons in collaboration with a global leader in robotic-assisted minimally invasive surgery.  The integrated solution will improve precision for tumor localization and differentiation from normal tissues to improve patient outcomes.  The successful applicant will have an opportunity to develop machine learning algorithms for real time clinical interpretation of in vivo fluorescence and photoacoustic images.  A portable platform will be used for fast processing speeds that will enable rapid clinical decision making in the operating room.  Training of deep learning models will be performed using datasets of images collected in vivo from human subjects.

Requirements: Candidates with a Ph.D. in computer science, engineering (e.g. electrical, biomedical, mechanical, aeronautics, etc), bioinformatics, statistics, or a related discipline with project experience in machine learning, deep learning, and natural language processing are invited to apply.  Programming experience with MATLAB, Python, and C++ is desirable.  International investigators are welcome.  Relevant skills include the following:

·   Expertise in relevant software programming languages

·   Experience with UNet architecture with MobileNet V2 backbone

·   Understanding of ResNet, Inception, and Xception.

·   Familiarity with Classification and Regression Tree (CART) and Random Forest (RF) methods

·   Proficiency in image denoising, motion artifact mitigation, and feature segmentation.

·   Knowledge of robotics systems, control systems, and systems engineering.

·   Excellent organizational and communication skills.

The Wang Lab at the University of Michigan is seeking a highly motivated Postdoctoral Research Fellow to design, fabricate, and characterize advanced microsystems scanning and actuation technologies for integration into next-generation miniature confocal, multi-photon, and photoacoustic endomicroscopes.  The successful candidate will join a multidisciplinary team working at the intersection of biomedical engineering, MEMS fabrication, and optical imaging.  This position focuses on the development of monolithic 3-axis micro-actuators for high-speed beam scanning in ultra-compact optical imaging systems.  Lead efforts to scale down device dimensions, optimize dynamic performance, and support multi-spectral, vertical-plane, and in vivo imaging with sub-cellular resolution.  Work directly supports development of flexible, fiber-coupled endomicroscope accessories for deep tissue imaging in preclinical models and translational clinical applications.  Collaborate with optical engineers to ensure alignment of optics and actuator within miniature imaging devices.  Provide technical mentorship to graduate students involved in scanner development and integration.

Responsibilities:

·       Design thin-film PZT micro-actuators for beam steering and axial translation.

·       Perform silicon wafer fabrication, thin-film PZT deposition, and lithographic patterning.

·       Execute deep reactive ion etching (DRIE) and XeF₂ etching.

·       Develop finite element models to simulate mechanical displacement, scan angle, and resonance modes.

·       Assemble multilayer micro-actuator stacks and integrate with optical components including reflectors, beam paths, and fiber optics.

·       Measure device static and dynamic deflections, frequency response, and displacement.

·       Develop calibration algorithms for real-time positional feedback using embedded piezoresistive sensors.

·   Conduct lifetime and reliability testing of batch-fabricated devices.

Qualifications:

·       PhD in Mechanical Engineering, Electrical Engineering, Biomedical Engineering, or a related field.

·       Experience in MEMS/NEMS fabrication, e.g. SOI wafers, comb-drive actuators, and wafer bonding.

·       Proficient in microfabrication techniques, e.g. photolithography, thin-film deposition, and DRIE.

·       Skilled in 3D MEMS design and characterization, including finite element modeling and CAD.

·       Experience with optical system design, micro-optics alignment, profilometry, and optical metrology.

·       Familiarity with feedback control systems and batch-scale prototyping for MEMS devices.

·       Strong analytical, organizational, problem-solving, written, and verbal communication abilities.

·   Proven publication record and ability to work both independently and in multidisciplinary teams.

Benefits:

·       Access to cutting-edge research facilities and professional development opportunities.

·       Salary commensurate with NIH guidelines and experience.

·       Full-time, 12-month appointment, renewable based on performance and funding.

·       Collaborative and supportive research environment.

The Wang Lab at the University of Michigan is seeking a highly motivated Postdoctoral Research Fellow to design, fabricate, and characterize advanced microsystems scanning and actuation technologies for integration into next-generation miniature confocal, multi-photon, and photoacoustic endomicroscopes.  The successful candidate will join a multidisciplinary team working at the intersection of biomedical engineering, MEMS fabrication, and optical imaging.  This position focuses on the development of monolithic 3-axis micro-actuators for high-speed beam scanning in ultra-compact optical imaging systems.  Lead efforts to scale down device dimensions, optimize dynamic performance, and support multi-spectral, vertical-plane, and in vivo imaging with sub-cellular resolution.  Work directly supports development of flexible, fiber-coupled endomicroscope accessories for deep tissue imaging in preclinical models and translational clinical applications.  Collaborate with optical engineers to ensure alignment of optics and actuator within miniature imaging devices.  Provide technical mentorship to graduate students involved in scanner development and integration.

Responsibilities:

·   Design thin-film PZT micro-actuators for beam steering and axial translation.

·       Perform silicon wafer fabrication, thin-film PZT deposition, and lithographic patterning.

·       Execute deep reactive ion etching (DRIE) and XeF₂ etching.

·       Develop finite element models to simulate mechanical displacement, scan angle, and resonance modes.

·       Assemble multilayer micro-actuator stacks and integrate with optical components including reflectors, beam paths, and fiber optics.

·       Measure device static and dynamic deflections, frequency response, and displacement.

·       Develop calibration algorithms for real-time positional feedback using embedded piezoresistive sensors.

·   Conduct lifetime and reliability testing of batch-fabricated devices.

Qualifications:

·   PhD in Mechanical Engineering, Electrical Engineering, Biomedical Engineering, or a related field.

·       Experience in MEMS/NEMS fabrication, e.g. SOI wafers, comb-drive actuators, and wafer bonding.

·       Proficient in microfabrication techniques, e.g. photolithography, thin-film deposition, and DRIE.

·       Skilled in 3D MEMS design and characterization, including finite element modeling and CAD.

·       Experience with optical system design, micro-optics alignment, profilometry, and optical metrology.

·       Familiarity with feedback control systems and batch-scale prototyping for MEMS devices.

·       Strong analytical, organizational, problem-solving, written, and verbal communication abilities.

·   Proven publication record and ability to work both independently and in multidisciplinary teams.

Benefits:

·   Access to cutting-edge research facilities and professional development opportunities.

·       Salary commensurate with NIH guidelines and experience.

·       Full-time, 12-month appointment, renewable based on performance and funding.

·   Collaborative and supportive research environment.