REHS Project Descriptions

If you are interested in computer science/engineering and enjoys event planning, then this internship is just for you! Working with the program manager, you will plan the ABLE program and implement a recruitment strategy for the coming year. Your work will include building an event calendar full of speaker conferences, campus lab tours, community activities, hands-on-workshops, and department lectures appropriate for this program. Additionally, you will plan for a meet up events for the ABLE participants. This internship will give you the rare opportunity to meet and network with campus faculties and community leaders as a high school student. It may be challenging at times when you have to plan multiple events simultaneously, but this will build your organizational skills. Apply today to plan some new, creative, and exciting events for the UCSD ABLE program!

Do you love working with students in a fun and informal setting? Do you like taking photos and being creative with Zoom? Then this summer opportunity is for you! Help the San Diego Supercomputer Center (SDSC) highlight our summer camp program to share with next year’s Summer student applicants and the community.

Wouldn’t it be helpful to be able to view a short video or view a photo album about a popular summer program before you apply to the program? We think so, too! Help us with this project and have your work immortalized on our SDSC webpages for years to come!

The successful student candidate will meet regularly with his/her mentor during the week to brainstorm and strategize successful video projects and photo albums. Join us for a fun and informative summer!r to create a compelling piece of work.  Join us and take the challenge!

The San Diego Supercomputer Center (SDSC) Education website has changed drastically over the last two years and now presents a sleek and modern design. Two items that are missing include and event calendar and a photo gallery. The current design was created by two former REHS students so please do not be nervous about applying for this opportunity.

The website was created using WordPress. WordPress skills are a MUST. If you are skilled in other website development software and feel that you can master WordPress without difficulty, please be prepared to share a single WordPress page during the interview process.

Students must possess:

Excellent written and oral communication skills

Previous experience working on a website or creating a website. 

Demonstrated proficiency with WordPress and/or demonstrated ability

Cancer is the second leading cause of death in the United States, and responsible for 580,350 deaths in 2013, it has become ever more imperative that researchers focus their attention in this field. Ingenuity Integrated Pathway Analysis (IPA) program is used to build and explore transcriptional networks, microRNA-mRNA target networks, phosphorylation cascades, and Protein-Protein or Protein-DNA interactions. We try to identify regulatory effects that lead from signaling events to transcriptional events for causal network analysis and to construct a comprehensive chart of diseases and functions associated with target genes so as to elucidate gene functionality and possible points of drug administration.

Are you interested in learning more about how researchers use websites and academic systems for their research? Are you interested in helping write about these researchers and highlighting them into a future published storybook? Then this summer opportunity is for you! Help the Science Gateways Center of Excellence (SGX3) write about science gateways and how they are solving research challenges and teaching the next generation of researchers.

Tasks will include conducting your own research about the science gateway, including looking at research papers and information on the science gateway’s public site; writing down findings in a digital document to be shared with your mentor; interviewing members of the SGX3 team to learn how SGX3 has supported this science gateway through consulting services; and writing a story about the science gateway. During the summer we will create several stories with the opportunity to prepare several stories for a future conference paper and to be included in our future storybook talking about outcomes of these science gateways.

The successful student candidate(s) will meet regularly with their mentor to review tasks and provide suggestions and feedback. The student candidate(s) will also have access to other communication channels to talk to other members of the SGX3 team via Slack and email.

This project involves running Jupyter Notebooks on the NSF funded Expanse high-performance (HPC) system [1] and testing software to be used on the NSF funded ICICLE AI project [3]. Expanse is SDSC’s newest supercomputer. The result of a $10M National Science Foundation (NSF) award, Expanse delivers over 5,2 peak petaFlOps of computing power to scientists, engineers, and researchers all around the world [2]. Expanse provides three kinds of HPC/CI resources: General Computing Nodes, NVIDIA GPU Nodes, and the petascale Luster filesystem. Thousands of users have accessed these high-performance computing (HPC) resources via traditional runs from the command line and using batch queuing systems.

The National Science Foundation funded AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE) [3] will build the next generation of Cyberinfrastructure to render Artificial Intelligence (AI) more accessible to everyone and drive its further democratization in the larger society. ICICLE will develop intelligent cyberinfrastructure with transparent and high-performance execution on diverse and heterogeneous environments. It will advance plug-and-play AI that is easy to use by scientists across a wide range of domains, promoting the democratization of AI.

Scientists using HPC Systems working with interactive HPC tools such as Jupyter notebooks to implement computational and data analysis functions and workflows [5]. Jupyter notebooks are web applications that allow you to create and share documents that contain live code, equations, visualizations and narrative text. These notebooks part of a general trend in research computing away from command-line style interfaces and towards browser-based and graphical interfaces. Jupyter notebooks are especially useful for interactivity: the development, testing, and exploration of data sets or as an instructional resource [6]. Users working interactively expect a timely response, both for initial application startup and during the course of a session.

The goals of this research project are:

1. To test and develop Jupyter Notebooks that run software components developed by the ICICLE project.
2. To learn the basics of  Jupyter notebooks, AI, and Knowledge Graphs.

The research components are:

1. Contribute to the body of knowledge needed for hosting live, dynamic, interactive services that interface to HPC systems
2. Learn how to develop interactive notebooks to be used for education and training of the users of these systems

Autistic Spectrum Disorders (ASD):
ASD is a neurodevelopmental disorder that includes social impairments, restrictive and repetitive behavioral patterns, and communication difficulties. Scientists have not found the cause for autism, however ASD is associated with both genetic and environmental factors. Autism is predicted to be caused by genetic mutations in critical neurological areas of the genome due to its etiological heterogeneity and likelihood in siblings. Specific genes and genomic loci have been located and implicated in ASD development. We study these gene interactions with the transcription factors that activate them and to find the spots of possible drug administration, molecular modeling and molecular dynamics simulations.

Alzheimer’s:
Alzheimer’s Disease is a neurodegenerative disorder that affects a variety of the brain’s functions, starting with short term memory loss, and eventually progressing to mood swings, disorientation, depression, and even loss of bodily functions. It is responsible for 60-70% of all dementia cases, and is the sixth leading cause of death in America. It is characterized by a buildup of β-amyloid plaques in the brain. There is no known cure for the disorder today, but recently, the amyloid hypothesis has been heavily researched as the mechanism of the disease. The amyloid precursor protein (APP) is cut by two enzymes, β-secretase and γ-secretase, and β-amyloid, the toxic form of the protein, is one of the segments that remains. Since the marker of Alzheimer’s is the buildup of this plaque in the brain, there is potential for slowing the progression of the disease if production of this protein is inhibited. We study existing drugs inactions with the target proteins and try to find methods to improve their action.

Cancer:
Cancer is the second leading cause of death in the United States, and responsible for 580,350 deaths in 2013, it has become ever more imperative that researchers focus their attention in this field. Ingenuity Integrated Pathway Analysis (IPA) program is used to build and explore transcriptional networks, microRNA-mRNA target networks, phosphorylation cascades, and Protein-Protein or Protein-DNA interactions. We try to identify regulatory effects that lead from signaling events to transcriptional events for causal network analysis and to construct a comprehensive chart of diseases and functions associated with target genes so as to elucidate gene functionality and possible points of drug administration.

The EarthCube Office strives to assist geoscientists and the wider research community through tools, methods, standards, architectures, and community connections. Our group seeks high school students that are interested in writing pieces related to EarthCube projects from start to finish. As a result of this internship, students will come away with an ability to reduce technical jargon and other barriers for the creation of easy-to-understand written pieces. Students will have the opportunity to choose a geoscience domain that is of interest to them and create both written and video pieces regarding that topic.

The Neuroscience Gateway (NSG – https://www.nsgportal.org) provides access to supercomputing resources for computational and cognitive neuroscientists. Through a simple web-based portal, the NSG provides a user-friendly environment for uploading models or data, specifying supercomputing job parameters, querying running job status, receiving job completion notices, and storing and retrieving output data. The NSG distributes user jobs to appropriate supercomputing resources. REHS students will learn about supercomputing and NSG during the initial period of the internship. Followed by that REHS students will be involved in either computational modeling of neurons using the NEURON software or processing of Electroencephalography (EEG) data using the EEGLAB software. In computational modeling scientists build models of neurons or network of neurons that perform various functions in our brain. NEURON is a widely used software for such modeling of neurons. Students will learn about a modeling project as part of their internship. EEG project involves recording of brain’s electrical activities tied to some function a subject is performing, and processing the data using software (such as the EEGLAB) and computing resources to see connection between brain signals and the function. Students will record and process EEG data as a part of their internship.

We are interested in students who have some background and interest in programming and scripting and are interested in neuroscience, computer science, data processing and modeling. Some experience with programming languages and exposure to Linux systems are preferred.

This project will use Jupyter Notebooks as the front end to a NoSQL database tracking the data center space used by current and future HPC systems at SDSC. Students working on this project will learn about data modeling, authentication and authorization using OAuth/OIDC, and generating various graphics in Jupyter Notebooks. Documentation will be a key part of this project, since it will be extended by SDSC staff in the future.
We are interested in students who have some background and interest in programming and scripting and are interested in neuroscience, computer science, data processing and modeling. Some experience with programming languages and exposure to Linux systems are preferred.

Our group seeks high school students who are interested in journalism with a focus on learning more about effectively communicating the results and societal benefit of science, engineering, and technological research projects. Candidates should have a strong desire to learn more about how to communicate technological research — with a keen eye for making the work both engaging and easily comprehended by a general audience. At the same time, students should be mindful of not diminishing the technical work of the research team in any way. Sound challenging?

As a result of this internship, students will come away with an ability to reduce technical jargon and other barriers for the creation of easy-to-understand written pieces. Students will have the opportunity to choose a science, engineering, and/or technological domain that is of interest to them and create written pieces regarding that topic as related to supercomputing.

Students will be assisted with both the science writing process as well as the final editing and completion of their articles with accompanying images, captions, and credits. 

In this project, we will explore how modern machine learning approaches can be employed in computational chemistry. As a background, the work in our lab encompasses computer simulations based on quantum chemistry and molecular dynamics. We develop numerical models and software for atomistic simulations of condensed phase systems and apply these to solve problems in the chemical sciences, ranging from atmospheric chemistry to biochemistry and drug design. Our focus has been on multiscale methods that couple computationally demanding quantum descriptions of the electronic structure with computationally simpler classical interaction potentials in so-called QM/MM methods. This enables numerical simulations of realistic models that are intractable with pure QM methods. The importance of such methods has been recognized with the award of the 2013 Nobel Prize in chemistry for “the development of multiscale models of complex chemical systems”. While machine learning approaches have a long history in computational chemistry, recent advances in data storage and compute capabilities have ushered in a new era of data-driven approaches, which we seek to explore and combine with existing QM/MM models. We are involved in the development of several software packages that are used by many research groups in academia and industry. This includes the quantum chemistry software packages ADF and QUICK and the molecular dynamics simulations package AMBER. Several other major codes that are deployed on major national computer resources are also an integral part of our work.

In this REHS project, the students will explore machine learning approaches that may improve the speed or enhance the accuracy of current state-of-the-art QM/MM simulation approaches. We will jointly work through online course material that introduces machine learning concepts from simple classifications to deep learning, culminating in applications that predict chemical properties. We will make use of Jupyter notebooks, the Python programming language, and widely used machine learning software frameworks. We will explore the performance of the software on CPU and GPU hardware including the Expanse supercomputer at SDSC. Time permitting, we will generate training data using quantum chemistry software and develop models that can predict new data without having to run the expensive QM simulations in the first place. The interns will thus have the possibility to acquire a wide range of skills in data science, computational chemistry, and high-performance computing. As an essential part of the internship the students will learn how to document their research, prepare research reports and present their results to their peers – skills that are very important for a successful research and engineering career.

Aggregation of specific proteins is associated with a number of diseases including Parkinson’s (PD), Alzheimer’s (AD), and other neurodegenerative diseases. Type II diabetes (T2D) is also linked to aggregation of Islet amyloid polypeptides (IAPP) IAPP is found to be significantly accumulated as extracellular amyloid deposits in the pancreas of T2D patients; it is shown that early oligomers are significantly cytotoxic species that lead to beta-cell apoptosis. The mechanisms through which IAPP leads to T2D are unclear. Various lines of evidence appeared to support the contention that IAPP oligomers built in the early stages of aggregation form annular protofibrils and consequently pores in the membranes the same way as amyloid-beta and alpha-synuclein correspondingly create pores in the cell membrane in AD and PD. Increase of calcium influx to the cells can lead to apoptosis in case of all these diseases.

The specific tasks of the project are using computer modeling and simulations to accomplish the following goals: (1) To characterize the interactions between IAPP, amyloid beta, and alpha-synuclein molecules in oligomers, and interactions between molecules and the membranes. (2) To validate a concept of self-assembly of these molecules, using a set of mutants known to enhance or inhibit IAPP aggregation process with identifiable structural properties.

The task will include extensive analysis of research articles in the field, related to modeling and simulations above mentioned proteins and their interactions with the membrane. Computational molecular modeling and molecular dynamics simulations.

The Open Science Chain (OSC – http://www.opensciencechain.org) project uses blockchain technologies to protect the integrity and provenance of research artifacts. The project is looking for summer interns who are interested in working with the OSC project. Interns will have the opportunity to engage in various tasks, including developing blockchain applications, revamping the web portal, or assisting in unit test development, depending on their interests and expertise levels.  Programming experience (Go, Java etc) and familiarity with Linux and container technology are preferred. This is a completely virtual internship. 

Deep neural networks (DNNs) have demonstrated great success in Machine Learning and Artificial Intelligence. However, the black-box nature of DNNs makes it hard to understand the underlying decision making process, which is crucial before DNNs can be deployed into real-world safety-critical systems. In this project, we will develop methods to understand DNNs in a human-understandable way.

Expanse is one of SDSC’s newest supercomputers. The result of a $26.5M award from the National Science Foundation (NSF), Expanse delivers more than 5 petaflops of computing power to scientists, engineers, and researchers all around the world. In its first two years of operations, Expanse has served over 5,000 unique users across more than 1,300 research projects spanning a range of scientific disciplines, becoming one of the most widely used supercomputers in the NSF’s Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program. 

The High-Performance Computing (HPC) User Services Group at SDSC helps manage user support across all of its HPC systems like Expanse. This includes, but is not limited to, building and maintaining an up-to-date end user software environment of high-performance compilers, advanced communication and math libraries, and domain-specific scientific applications that are optimized for each system’s unique hardware capabilities. On Expanse, the User Services Group is developing a new software deployment process using Spack, an open-source software package management tool that is designed to simplify and accelerate the building, installation, and customization of large, complex scientific and high-performance computing software environments. While the current production software environments available on Expanse are managed by Spack, the deployment and maintenance of each environment remains a largely manual and less-than-efficient, somewhat error-prone process.

The aim of this research project is to optimize and improve the Spack-based software deployment process on SDSC’s HPC systems. During the course of this project, you will learn how to:

• install software with Spack,
• schedule and run software build jobs on SDSC’s supercomputers like Expanse via the Slurm workload manager, and
• analyze and present benchmarking results for these build jobs.