Undergraduate Summer Research Fellow (DSI-SRP Fellowship)
Dr. Todd Giorgio
Whole genome sequencing has advanced from a whole organism technique to the current practice that enables genomic decoding from thousands of individually addressable, single cells. The volume of this single cell RNAseq (scRNAseq) information can be very large with practically limitless opportunities to explore relationships and test hypotheses. We have acquired scRNAseq from mammary fat pad tumors in mice to examine the role of olfactory receptors (ORs) in breast cancers. Preliminary scRNAseq analysis confirms experimental studies, earlier DNA microarray data and a recently published study from our lab (1) conducted using The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE) in identifying specific ORs associated with tumor-associated macrophages.
We seek an undergraduate student with an interest in the hypothesis-testing and visualization of scRNAseq data for breast cancer research. We expect to conduct additional scRNAseq experimental studies during summer 2020, enabling candidates the potential to combine the laboratory aspects and computational approaches of scRNAseq.
Our previous work has been principally conducted using custom scripts prepared in Python and R; preference is for candidates having familiarity with these tools. An alternative to the use of Python and R would be a comparison among the numerous and growing open source scRNAseq analysis and visualization tools in the interpretation of our data.
Must apply as part of the DSI-SRP program to be eligible.
Contact: Dr. Todd Giorgio for more information
Data Scientist (intermediate)
Imaging application modeling using computer vision and deep learning for images from various platforms. Work cross-functionally with teams of researchers. You will spend some time on image clean up and image annotation work when necessary.
What You Will Do:
– Conduct research projects to create curated datasets, formulate machine learning problems, and apply machine learning and computer vision techniques to solve real agronomic problems.
– Work in a highly collaborative environment with other data scientists, agronomists, pathologists, engineers to deliver systems from prototyping to production level.
– More than 2 years’ experience with a focus on computer vision, deep learning or related fields
– Experience in machine learning and deep learning framework such as Tensorflow, Pytorch and solid programming development skills (Python, Scala, etc)
– Excellent problem-solving, troubleshooting, and communication skills
– Hands-on experience with machine learning training on infrastructures and frameworks such as GPUs, Spark, distributed Tensorflow etc
– Strong drive to learn new topics and skills, to develop innovative products for our customers, and build whatever is necessary along the way
Neteffects is an IT Staffing Company. *Neteffects processes visas and green cards*
Vanderbilt Dermatology Translational Research Clinic
Two post-doctoral scholar positions. The goal is to develop, commercialize, and deploy technologies in our ongoing multicenter trials to track disease progression and response to treatment following stem cell/bone marrow transplantation.
1. Skin Mechanics
2. Analysis of rash images
Eric Tkaczyk, M.D., Ph.D.