Online Master's in Biomedical Engineering @ Case.edu
A Mighty Force - read full story

2020 Undergraduate Opportunities

 

Due to COVID-19, many of our undergrad students have lost their summer internships and other opportunities. Below are "remote-ready" opportunities that have been identified as alternatives.

 

Check back soon! We will updated this page as more opportunities become available.

 

 


 

 

Remote Research

 

Conversational Agents for Medication Management

Background: The overall goal of this research is to better understand how technology can play a role in assisting patients in community settings manage multiple medications, specifically to improve polypharmacy outcomes. In-home patient self-management of polypharmacy medication and all relative contraindications is mentally burdensome and the risks of missing or mismanaging medications are both costly and potentially unnecessarily life-threatening.  Medication errors are possible even in the common situation where home care support involves trained family members or home care nurses visiting 2-3 times a week.  This project is centered on the development of a novel decision-support system based on an interactive voice-activated advisory system ( a so-called “conversational agent” Alexa) based to assist patients with self-management of medications.

Task: We have started exploring and testing the ability of Alexa Skills to provide voice-response to patient conversation about medication usage.  We would like to test the implementation of medication schedule input  into an Alexa Skill, addressing the nuances of PRN medications and contraindications.
Capabilities needed: computer, internet to remote-desktop into lab computer, at least intermediate familiarity with coding (in any language, but particularly JSON), good code management and willingness to learn Alexa Skills.

Paid or Volunteer: Volunteer

Contact: Colin K. Drummond (colin.drummond@case.edu)

 

Evaluating sensitivity of inter-reader variations in delineating regions of interest on prostate MRI in training machine learning models

Background: In designing predictive machine learning models with medical imaging data, a large number of annotated patient studies are needed. There is always some amount of inter-reader variations in delineating regions of interest (ROIs) on imaging. This variability is often a bottleneck to develop models that can be generalized.

Task: The student will be engaged in analyzing multi-site prostate MRI data and evaluate the sensitivity of machine learning models trained for specific tasks to the ROIs delineated by multiple readers.

Skillset needed: Basic image processing, machine learning, data sorting and organization; familiarity with Matlab/Python is a plus

Contact: Dr. Rakesh Shiradkar (rxs558@case.edu )

 

Designing optimal patient specific 3D prostate molds using in vivo MRI

Background: Gold standard for disease diagnosis is pathologic specimen, which however involves invasive procedures. With expanding potential of AI based method and technologies, non-invasive imaging based diagnosis are being increasingly studied and researched which require a well annotated training dataset. Patient specific 3D molds allow for generation of a near perfect ground truth that could be used for training AI based models.

Task: Prostate delineations on in vivo MRI will be used to optimally design 3D molds using commercial CAD software accounting for post-surgical changes in the prostate. If possible, the student may also be engaged in evaluating alignment of post-surgical tissue specimen with in vivo prostate on MRI.

Skillset needed: Basic image processing, 3D volumetric analysis, familiarity with CAD software – although none of these are prerequisites.

Contact: Dr. Rakesh Shiradkar (rxs558@case.edu)

 

Evaluate stain estimation approaches for digital pathology images

Background: Tissue samples are often stained with 2 or more samples before they are digitized. Each of these stains is designed to highlight specific components of the image, from nuclear regions to potential cancerous tissue. Once digitized, it becomes invaluable to be able to accurately extract each stain individually from the RGB image to aid in the downstream computational analysis of images.

Task: Using the large inhouse datasets that we have, evaluate various open-source tools employed in the separation, or “deconvolution” of images, to provide guidance into the algorithms used in our other experiments

Capabilities needed: computer, internet to remote-desktop into lab computer, introductory python skills, elementary image analysis skills

Paid or Volunteer: Volunteer

Contacts: PI: Prof.  Andrew Janowczyk (axj232@case.edu)

 

 

Dataset minimization of digital pathology images for training deep learning classifiers

Background: In the digital pathology domain, obtaining large quantities of labeled data is often a limiting factor of experimental success. At the same time, not all training data is of similar quality, with some exemplars proving to be significantly more “information-rich” and useful in the improvement of deep learning classifiers.

Task: We have existing code for training deep learning classifiers, and large numbers of datasets which are built with randomly selected patches from large (100k x 100k) digital pathology images of cancer. We would like to systematically remove training examples from the dataset, using various information metrics, to find the minimal set of training examples needed to sustain classifier performance. Afterward, this metric will be employed prospectively to guide data sampling efforts.

Capabilities needed: computer, internet to remote-desktop into lab computer, intermediate python skills, elementary image analysis skills, machine or deep learning skills a significant plus

Paid or Volunteer: Volunteer

Contacts: PI: Prof.  Andrew Janowczyk (axj232@case.edu)

 

 

 

Drug delivery and cellular binding in the tumor spheroid

Background: The spheroid is a 3D multicellular model of the tumor microenvironment. It mimics many aspects of tumor tissue in vitro. The spheroid model is extensively used in drug development to improve drug efficacy and in personalized medicine to predict the best treatment for individual patients.

Task: The goal of this project is to develop a mathematical model of drug penetration in spheroids taking into account also concurrent cellular uptake and binding. Such model has not been created before.

Capabilities needed: Intermediate capability of coding in Matlab or another suitable coding language.

Contact: Prof. M. Gratzl (mxg13@case.edu)

 

 

Drug delivery and cellular binding in the capillary model of the tumor microenvironment

Background: The spheroid is an established 3D in vitro multicellular model of the tumor microenvironment. An alternative is the novel capillary model whose structure is entirely different from the spheroid’s but it is expected that it will perform better for vascularized solid tumors than the spheroid which is more suitable for mimicking nascent avascular tumors.

Task: The goal of this project is to develop a mathematical model of drug penetration taking into account also concurrent cellular uptake and binding in the capillary tumor tissue model. The capillary model is itself new and therefore, its mathematical modeling has never been attempted before.

Capabilities needed: Intermediate capability of coding in Matlab or another suitable coding language.

Contact: Prof. M. Gratzl (mxg13@case.edu)

 

 

Oral Appliance for OSA

Task: From the XRay and Dental scan a patient, design an appliance in SolidWorks specific to that patient. The appliance will be  3D printed

Contact: Grant McCallum  gam19@case.edu

 

 


 

Opportunities from SOURCE

 

 

Parker Dewey remote micro-internships

Parker Dewey is an online platform that connects you with  short-term, professional, paid work experiences through micro-internships which can be completed remotely. 

Through micro-internships, you can demonstrate your skills, explore career paths, and develop your professional networks. These paid opportunities typically range from 5 to 40 hours of work, and you can be selected for multiple micro-internships.

New micro-internship opportunities are being posted daily. Follow these steps to get started: 

  1. Create an account at info.parkerdewey.com/cwru
  2. Fill out your profile as completely as possible
  3. Review available micro-internship projects
  4. Apply to projects of interest
  5. Continue to check the platform regularly for new opportunities

If you need assistance applying for a micro-internship, schedule an appointment with a career and internship consultant in Post-Graduate Planning and Experiential Education. 

 

 

Summer on the Cuyahoga

Summer on the Cuyahoga (SOTC) is a unique summer internship program open to students who are rising juniors, rising seniors and recent graduates and attend one of our eight partner schools: Case Western Reserve, Colgate, Cornell, Denison, Oberlin, Ohio Wesleyan, Smith, and University of Chicago. The program brings together 60-70 students for an intensive summer immersion program designed to help interns explore the professional, civic and social offerings of the Cleveland area. SOTC offers students challenging internships, numerous events/activities, community introductions, alumni connections, and FREE group housing for the summer.