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Student R&D Opportunities

Biosciences
Evaluation and Development of NASA GeneLab Data Processing Pipelines
Overview

Up to 6 interns will be selected for this internship and will be split into 3 groups. Each group will work on one of the following 3 projects. In your cover letter, please rank the 3 projects listed below from most to least interesting to you, why you are interested in this internship, what you hope to gain from the internship, and what makes you qualified for this internship. Please provide links to a cover letter, your CV and an unofficial transcript. Provide a link to your unofficial transcript in the last question (i.e. additional materials). 

Projects
  • Remove Duplicates using UMIs: Process datasets containing Unique Molecular Identifiers (UMIs), then compare the results if you remove duplicates vs keeping them in.
  • In silico rRNA Removal: Select two sets of GeneLab datasets (set 1: datasets where most samples contain high rRNA contamination; set 2: datasets containing very few samples with high rRNA contamination) and re-process them but this time remove rRNA with HTStream - compare the results to those without removing rRNA. Next, compare HTStream rRNA removal (k-mer based) vs. removing rRNAs with an aligner (i.e. STAR) based removal process.
  • Single-Cell (and/or Spatial Transcriptomic) RNAseq processing: Help develop and test pipelines for processing single-cell RNA sequencing data and/or Spatial Transcriptomics data.
Prerequisites
  • Successful completion of San Jose State University's Bioinformatics ll (Biol 23B / CS 123B) course
  • Successful completion of the GeneLab RNAseq bootcamp
  • Good academic standing
Degree level

Undergraduate level (enrolled San Jose State University student)

Opportunity Type

Internship

Aeroflightdynamics
Human Systems Interface
Overview

The SUMIT data analysis is underway and needs assistance with simple data entry. This data entry position is specifically to format and enter the questionnaire data collected from the pilot’s questionnaire data (both numerical and text) into excel spreadsheets so that it can be formatted into SPSS and work with the mentor on doing the analysis. SPSS is a statistical analysis software (link).

Skill Set
  • Candidate should possess extremely high attention to detail for example, interpreting the pilot's handwriting and entering that data accurately and correctly
  • Familiarity with SPSS and data analysis techniques such as ANOVA, ANCOVA, T-tests
  • Good math and statistics background
  • Candidate should be available to start mid-January 2020
Aeronautics
AEGIS INTERN (Autonomous Entity Global Intelligence System)
Overview

This project is to develop a nominal prototype of an “Autonomous Entity Global Intelligence System” or AEGIS, by incorporating cutting edge Artificial Intelligence (AI) and Machine Learning (ML) technologies to enable a distributed supervisory control framework for Urban Air Mobility (UAM). In this project, the student will apply cutting-edge AI/ML technology to make real-world aviation and coordination among autonomous air vehicles efficient and safe. The intern will deliver working data synthesis, simulation, and visualization modules in the form of software codes.

This position will consist the following tasks:

  • Create representative sets of operation scenarios, by synthesizing existing aeronautics and aviation data
  • Develop a machine learning model for analyzing and inferring the synthesized data
  • Setup a simulation testbed to ingest, engineer, infer the data, and visualize the simulation results
  • Implement and evaluate multiple operational modes in different unconstrained and constrained scenarios
Skill Set

To accomplish this work, the intern requires proficiency with software technologies in one of the following two categories:

Category A

  • Desired skills: D3.js, MATLAB, C/C++
  • Additional preferred skills: Visual Studio, Unity, Adobe Illustrator
  • Experience level: 0-5 years

Category B

  • Desired skills: Python, MATLAB, Tensor Flow, CUDA
  • Additional preferred skills: KERAS, Open CV, Unity
  • Experience level: 0-5 years

Additional general expectations include:

  • Ability to work in small teams
  • Excellent oral and written communication skills
  • Being in a software engineering, preferably computer science, degree program
Degree level

Graduate level (enrolled University Student)

Opportunity Type

Internship

Urban Air Transport Research and Development
Overview

The Air Traffic Management Exploration (ATM-X) project will develop and demonstrate a new service-based air traffic system paradigm. NASA researchers are exploring an initial concept development of Urban Air Transport Disruption Management platform (UATDM). UATDM aims at enabling highly automated commercial services provided by Unmanned Aircraft Systems and Urban Air Mobility in low-altitude airspaces. The selected interns will have the opportunities to perform researches and develop algorithms for UATDM.

Expected opportunity outcome

Research, poster presentation, numerical models or algorithms, report or conferences/journal publications

Skill Set
  • Mobile App development knowledge or experiences in Matlab/C/C++/Java/Optimal controls/machine learning
Degree level

Undergraduate level student (Senior level – pursuing BS) / graduate level student (MS year 1-2)

Opportunity Type

Internship (part-time)

Unmanned Aerial Systems (UAS) Research
Overview

This work supports the UAS in the National Airspace System (NAS) integration project. The goal is to characterize detect and avoid (DAA) system behavior and identify / extract scenarios of interest in order to further the project's research objectives.

To accomplish this, the work will focus on visualization and analysis of DAA encounters between UAS and manned traffic operating under visual flight rules.

Degree level

Undergraduate level student (Senior level – pursuing BS) / graduate level student (MS year 1-2)

Opportunity Type

Internship

Unmanned Aircraft System Traffic Management (UTM) Research
Overview

The UTM (Unmanned Aircraft System (UAS) Traffic Management (UTM)) research platform enables the testing of various capabilities ranging from visual line-of-sight operations in rural areas to beyond visual line-of-sight (expanded) operations in urban areas. This platform is comprised of a set of web services that are accessible from a remote server by clients that have been implemented according to the published interface control document (ICD). The ICD defines the communication between the UTM research platform and an operator. It provides the information necessary to develop clients and software applications that interface with the UTM research platform.

The UTM research team has developed a number of clients and applications that displays UTM information and enables interaction with the UTM research platform. The goal is to distribute this client software to as many universities as possible and assist them in communicating with the UTM server at NASA Ames to help enhance the UTM concept development and provide a wider base for research within the academia in this field.

Degree level

Undergraduate level student (Senior level – pursuing BS) / graduate level student (MS year 1-2)

Opportunity Type

Internship

General
USRA-NAMS Student internship at NASA Ames Research center
Overview

USRA's R&D Student Program supports projects at NASA Ames as part of the NASA Academic Mission Services (NAMS). The goal of these internships is to help advance the milestones of the project and to help complete the student's thesis.

The internships range in technical areas of:

  • Aeronautics
  • Earth Science
  • Data Science
  • Machine Learning
  • Robotics
  • Synthetic Biology
  • Biosciences
  • Environmental Analytics

The internships are offered part time during the school year and full time during the summer. The students will work alongside USRA and NASA PI(s) at the NASA Ames Research Center. We encourage students to continue their education in Science, Technology, Education and Math (STEM) fields either within the government, academia, or industry.

Degree level

Graduate level (enrolled University Student)

Opportunity Type

Internship