Graduate Research Assistantships for Fall 2020 Term in Computational Multiphase/Multi-Physics Projects

By | News, SC2 jobs

Professor Jesse Capecelatro’s Computational Multiphase/Multi-Physics Flow Lab is seeking Three Graduate Students

 

Professor Jesse Capecelatro is a faculty member within the College of Engineering’s Mechanical and Aerospace Engineering departments. Prof. Capecelatro’s lab group is seeking current or recently graduated Master’s or Ph.D. students for paid Research Assistant positions starting in the Fall 2020 term. Read more about Prof. Capecelatro’s research group here.

Research Assistants will be working on one of three projects.

PROJECT #1: MODELING TURBULENT FLOWS WITH FINITE SIZE PARTICLES ON HETEROGENEOUS ARCHITECTURES

Description: The objective of this project is to develop a highly scalable direct numerical simulation (DNS) code that leverages new algorithmic advances in (a) turbulence simulation using a pseudo-spectral approach on heterogeneous architectures and (b) efficient scaling of particle dynamics with number of particles, to perform massive-scale simulations with a mixture of CPUs and GPUs. The student will work with Prof. Capecelatro at UM and collaborators at Iowa State and Georgia Tech. The majority of the code will be written in Fortran 90 and C.

This position is expected to last 1 year in duration with the possibility of extension, and work will be performed remotely. Compensation for this position will be based on experience and qualifications.

Desired Qualifications:

  • Major in Mechanical Engineering, Computer Science, or similar
  • Strong background in fluid mechanics
  • Good knowledge in turbulence
  • Excellent programming skills in a high-performance language like C, Fortran, Python
  • Familiar with parallel computing

PROJECT #2: MULTI-STEP EFFECTIVENESS FACTORS FOR NON-SPHERICAL CATALYSTS

Description: Prof. Capecelatro and his postdoc Aaron Lattanzi will provide support to the graduate student on development of new models for diffusion limited reaction schemes that will be delivered to the National Renewable Energy Laboratory (NREL). The multi-step effectiveness vector (MEV) previously derived by CO-PI Lattanzi will be expanded to account for cylindrical and infinite slab catalyst geometries. Reactant concentration profiles and volume-averaged reaction rates predicted by the new MEV will be directly compared to high-fidelity simulations conducted by NREL to verify the model.

This position is expected to last 9 months in duration with the possibility of extension, and work will be performed remotely. Compensation for this position will be based on experience and qualifications.

Desired Qualifications:

  • Major in Chemical Engineering, Mechanical Engineering, or similar
  • Excellent programming skills in a high-performance language like C, Fortran, Python
  • Strong background in fluid mechanics
  • Familiarity with chemical kinetics (CHE 344. Reaction Engineering and Design or similar class)

PROJECT #3: SENSITIVITY AND UNCERTAINTY QUANTIFICATION OF MODELING PARAMETERS FOR SIMULATING HIGH-SPEED MULTIPHASE FLOWS

Description: The student will perform a literature review on the state-of-the-art in modeling compressible particle-laden flows. Simulations will be performed of shock waves interacting with solid particles using our in-house high-speed multiphase flow solver (Fortran 90). A sensitivity analysis will be performed to quantify the effect of particle statistics on modeling parameters.

This position is expected to last 9 months in duration with the possibility of extension, and work will be performed remotely. Compensation for this position will be based on experience and qualifications.

Desired Qualifications:

  • Major in Aerospace Engineering, Mechanical Engineering, or similar
  • Excellent programming skills in a high-performance language like C, Fortran, Python
  • Familiar with uncertainty quantification, tools for sensitivity analyses
  • Strong background in fluid mechanics
  • United States citizenship

APPLY  TODAY!
Please send your CV, transcript, and a brief statement about your interests and background relative to the projects listed above to Professor Jesse Capecelatro jcaps@umich.edu with subject, “Fall 2020 Research Assistantship”.

Graduate Research Assistantships for Fall 2020 Term in Physics-based Data-driven Modeling Projects

By | News, SC2 jobs

Professor Julie Young’s Lab Seeking Two Engineering-focused Grad Students to Assist in Modeling Research

Professor Julie Young is a faculty member within the College of Engineering’s Naval Architecture and Marine Engineering, Mechanical Engineering, and Aerospace Engineering departments. Professor Young’s lab group is seeking graduate students (current or recently graduated master’s or Ph.D.’s) for paid Research Assistant positions starting in the Fall 2020 term. The expected time commitment for these positions is 20 hours per week.

Students will be working on one of two projects:

Project #1 Description: Development of a physics-based data-driven model for system identification and control of lifting surfaces in multiphase flow.

Project #1 Desired Qualifications:

  • Excellent programming skills
  • Good knowledge of system identification
  • Familiarity with data-driven models, control methods
  • Familiarity with experimental modeling and data analysis
  • Good knowledge of nonlinear fluid and structural dynamics
  • Engineering major or extensive coursework in engineering-related field
  • United States citizenship

Project #2 Description: Development of physics-based data-driven model for marine ship-propulsion system.

Project #2 Desired Qualifications:

  • Excellent programming skills
  • Good knowledge of system identification and data-driven models
  • Familiarity with experimental modeling and data analysis
  • Good knowledge of propulsion systems
  • Engineering major or extensive coursework in engineering-related field
  • United States citizenship

Compensation:
Compensation for these positions will be commensurate with experience and qualifications.

Apply Today!
Please send your CV, transcript, and a brief statement about your interests and background relative to the projects listed above to Professor Julie Young at ylyoung@umich.edu with subject, “Fall 2020 Research Assistantship”.

Computational Biologist Postdoc-level Opening in Microbial Genomics

By | News, SC2 jobs

Air Force Research Labs Seeking Postdoc-level Computational Biologist for Microbial Genomics Position

 The Air Force Research Laboratory near Dayton, OH is seeking a Computational Biologist with experience in microbial genomics. The successful candidate will have the opportunity to work across multiple collaborative projects in the areas of microbial biofouling and corrosion, polymicrobial interactions of DoD relevant microbial communities, and mechanisms of polymer biodegradation. The selected candidate will use informatics to assemble, annotate, and perform comparative analyses of both bacteria and fungi to aid in generation of testable hypotheses. This role requires effective teamwork and communication of results with colleagues from diverse backgrounds.

Functions for this Role will also Include:

  • Transcriptomics of bacteria and fungi communities including differential expression analyses and identifying upregulated proteins
  • Analysis and interpretation of microbial community data using network analyses and visualization tools
  • Informatics on enriched and complex microbial communities generated from metagenomics and metatranscriptomics including assembly, binning, annotation, enzyme mining, and phylogenetic analyses
  • Documentation and presentation of research progress in the forms of reports, publications, and oral presentations
  • Travel to scientific reviews and conferences

Required Qualifications:

  • Ph.D. (or M.Sc. with 5+ years of relevant experience) in Computational Biology, Bioinformatics, or Microbial Genomics
  • Demonstrated success in applying open source software and in developing novel algorithms for the comparative analysis of genomes
  • Deep understanding of phylogenetic analyses and comparative genomics methods
  • Fluent in major scripting languages such as Python or Perl, and proficient in using the command line in Unix environments
  • Previous experience in comparative genomics or an understanding of secondary metabolite biosynthesis is highly desirable
  • Experience in applying machine learning algorithms or statistical methods to solving biological problems is desirable
  • Demonstrated understanding of relevant public genomic databases
  • Ability to work effectively in a multidisciplinary team, and communicate results clearly to non-computational scientists
  • Excellent organizational skills
  • This position is working on-site at a government facility and requires U.S. citizenship

Apply Today!

Apply via this link: https://ues.hrmdirect.com/employment/job-opening.php?req=1328012&&cust_sort1=-1&&nohd#job

If you have any questions, please email eric.harper.4@us.af.mil and vanessa.varaljay.1@us.af.mil.

1-3 Year Postdoc Opportunities with the Center for Exascale Monte Carlo Neutron Transport

By | News, SC2 jobs

Positions in Computational Science Research, Code Development, and Student Mentoring Support at Oregon State University and the University of Notre Dame

The Center for Exascale Monte Carlo Neutron Transport (CEMeNT) is recruiting for two postdoctoral scholars to provide computational science research, code development, and student mentoring support. These positions are full-time, 12-month Postdoctoral Scholar positions: one located in Corvallis, Oregon, working within the School of Nuclear Science and Engineering at Oregon State University, and one located in South Bend, Indiana, working within the Department of Aerospace and Mechanical Engineering at the University of Notre Dame. Funding for these positions is expected to exist for three years; however, contracts are annual and are eligible for extension based on satisfactory performance and mutual agreement.

CEMeNT is a competitively designated National Nuclear Security Administration funded Focused Investigatory Center as part of the Predictive Science Academic Alliance Program (PSAAP – https://share-ng.sandia.gov/psaapIII/). Within CEMeNT, researchers from Oregon State University, the University of Notre Dame, and North Carolina State University work to develop the mathematics, computational physics, and computer science required to scale time-dependent Monte Carlo neutron transport simulations to exascale-class computers. Our work has high visibility in the US National Laboratories and the computational science community.

The universities participating in CEMeNT commit to inclusive excellence by advancing equity and diversity in all that we do. We are Affirmative Action/Equal Opportunity employers, and particularly encourage applications from members of historically underrepresented racial/ethnic groups, women, individuals with disabilities, veterans, LGBTQ community members, and others who demonstrate the ability to help us achieve our shared vision of a diverse and inclusive community.

Responsibilities:

  • Collaborate with the CEMeNT Leadership and CEMeNT-affiliated faculty to conduct cutting edge research in computational and develop software for solving neutron transport problems on world-leading architectures.
  • Advance the state-of-the-art in Monte Carlo particle transport, hybrid methods, uncertainty quantification, and/or machine-learning enhanced physics simulation.
  • Work alongside colleagues at US National Laboratories to further the impact of the research and development at CEMeNT.
  • Mentor and direct the research work of graduate students.

Required Qualifications:

  • Ph.D. in nuclear engineering, mechanical engineering, computational physics, applied mathematics or scientific computing disciplines.
  • Proven track-record of independent research, critical thinking, and successful academic publications.
  • Excellent written and verbal communication skills.
  • Experience in developing software for high performance computing
  • applications using Python and C++.
  • A demonstrable commitment to promoting and enhancing diversity.

Preferred Qualifications:

  • Ph.D. in nuclear engineering, mechanical engineering, computational physics, applied mathematics or scientific computing disciplines.
  • Proven track-record of independent research, critical thinking, and successful academic publications.
  • Excellent written and verbal communication skills.
  • Experience in developing software for high performance computing
  • applications using Python and C++.
  • A demonstrable commitment to promoting and enhancing diversity.

Position available: August 14, 2020 (open until filled) U.S. citizens and residents will be prioritized.

Stipend and benefits conform with postdoctoral scholar standards at Oregon State University and Notre Dame University. More information about postdoctoral scholar appointments can be found at the Office of Postdoctoral Scholars at ​Oregon State University​ and the ​University of Notre Dame​.

Apply Today!

For full consideration, apply by August 7, 2020. Applicants must send the following documents in a single PDF file (Word documents will not be opened) to ​both contacts​ listed below:

  • A detailed CV and academic transcript
  • A one-page statement describing your background and how you fit the
  • advertised position. Please specifically reference the required and preferred qualifications.
  • Contact information for three references
  • The subject line of your email should contain the following text: “CEMeNT Post-doctoral Scholar – (your last name).” Please note that only candidates that meet the required skills and expertise will be contacted.

Contacts

Dr. Todd Palmer, CEMeNT Director (todd.palmer@oregonstate.edu); School of Nuclear Science and Engineering Oregon State University

Dr. Ryan McClarren, CEMeNT Deputy Director (rmcclarr@ndu.edu); Department of Aerospace and Mechanical Engineering University of Notre Dame

Computational Biologist Postdoc-level Opening in Bioinformatics

By | News, SC2 jobs

Air Force Research Labs Seeking Postdoc-level Computational Biologist for Bioinformatics Position

The Air Force Research Labs at the Wright-Patterson Air Force Base is seeking a Computational Biologist with experience in bioinformatics and machine learning. The Computational Biologist will have the opportunity to work on novel microbial degradation of perfluoroalkyl (PFAS) compounds using genomics, enzyme mining, and AI/ML. The successful candidate will use bioinformatics and AI/ML to identify biological PFAS degradation pathways and enzymes to aid in the generation of testable hypotheses for wet-lab experiments. This role requires effective teamwork and communication of results with colleagues from diverse backgrounds. 

Functions for this Role will also Include:

  • Bioinformatics on enriched and complex microbial communities generated from metagenomics including assembly, binning, annotation, enzyme mining, and phylogenetic analyses
  • Applying AI/ML for identifying optimized biological modes of PFAS degradation
  • Documentation and presentation of research progress in the forms of reports, publications, and oral presentations
  • Periodic travel to scientific reviews and conferences

Required Qualifications:

  • Ph.D. (or M.Sc. with 5+ years of relevant experience) in Computational Biology, Bioinformatics, or Microbial Genomics
  • Fluent in major scripting languages such as Python or Perl, and proficient in using the command line in Unix environments
  • Experience in applying machine learning algorithms or statistical methods to solving biological problems
  • Deep understanding of phylogenetic analyses and comparative genomics methods
  • Demonstrated understanding of relevant public metagenomic databases
  • Ability to work effectively in a multidisciplinary team, and communicate results clearly to non-computational scientists
  • Excellent organizational skills
  • This position is working on-site at a government facility and requires U.S. citizenship

Apply Today!

Apply via this link: https://ues.hrmdirect.com/employment/job-opening.php?req=1328011&&cust_sort1=-1&&nohd#job

If you have any questions, please email eric.harper.4@us.af.mil and vanessa.varaljay.1@us.af.mil.

Air Force Research Labs Seeking Student Research Assistant for Bioinformatics and Machine Research Project

By | News, SC2 jobs

Research Assistant in Bioinformatics and Machine Research Opportunity for the Fall 20 – Winter 21 Academic Year + Possibility of Summer Extension

The Air Force Research Labs at the Wright-Patterson Air Force Base is seeking a Student Research Assistant to contribute to a project that combines bioinformatics and machine learning. Upper-level undergraduate students, Master’s students, and recent graduates are encouraged to apply.

Position Details: 

  • The expected time commitment for this position is ~10 hours/week for the Fall 2020 and Winter 2021 terms, with the opportunity to work full time in the summer of 2021.
  • This position will work remotely throughout the academic year, with the possibility of working on-site next summer at the Wright-Patterson Air Force base near Dayton, Ohio.
  • This position will be co-advised by two AFRL researchers.
  • Compensation will be commensurate with experience and education.

Required Qualifications:

  • Applicants for this position should have an interest and/or familiarity with biology or data analysis and machine learning, with an academic major or concentration in one of the following science or engineering fields:
    • Biology, Chemistry, Computer Science, Data Science, Information
    • Biomedical Engineering, Chemical Engineering, Materials Science & Engineering, Computer Science and Engineering, Electrical Engineering and Computer Science

Apply Today!

To apply for this position, please email eric.harper.4@us.af.mil and vanessa.varaljay.1@us.af.mil with a brief resume or CV.

Seeking Student for Fall 2020 Research Project in GPU Programming for HPC Simulations of Quantum Systems!

By | News, SC2 jobs

Seeking Student for Fall 2020 Research Project Position with the U-M Computational Quantum Many-Body Physics Group

The U-M Computational Quantum Many-Body Physics Group, led by Professor Emanuel Gull,  is seeking a master’s student to contribute to its work on a research project in graphics processing unit (GPU) programming for high-performance computing (HPC) simulations of quantum systems. Qualified undergraduate students may also be considered for this position. Don’t miss out on this great opportunity!

Position Details: 

  • Knowledge of physics and quantum mechanics is not required for this position
  • The estimated workload for this position is 10-20 hours per week
  • Tentative start date: Fall 2020 term on the University of Michigan’s Ann Arbor campus

Required Qualifications:

  • Experience working with CUDA parallel computing platform and related techniques
  • Familiarity with HPC, scaling, and optimization strategies

Compensation:

  • Compensation range for this position is $20-$25, commensurate with experience and qualifications

Apply Today!

Please send a brief (no longer than 2-page) CV or resume to Professor Emanuel Gull at egull@umich.edu with subject, “Fall 2020 Project Research Assistant Position”.

Graduate Student Lab Positions Available at Concordia University (Canada)

By | SC2 jobs

Looking for Grad Students interested in Physics-Based Design of Therapeutics!

There are 1-3 openings for fall or winter 2020/2021 in Professor Ré Mansbach’s lab. Professor Mansbach is starting the lab in the Physics Department at Concordia University (http://www.concordia.ca/artsci/physics.html) in Montreal, Quebec, CA. There will be an associated tuition waiver and stipend for highly qualified/talented students.

Desired qualifications:  Looking for highly motivated graduate student candidates interested in theoretical and computational biophysics and deep learning.  Physics or Biophysics BA or BS is preferred but CS, biomedical engineering or related fields are welcome to apply. Experience with coding will be valuable, particularly in Python, and prior experience with molecular dynamics simulations will also be useful. 

Overview of Scientific Goals: Proteins are the building blocks of living things, miniature motors that make all of your cells function. Proteins embedded in cell membranes filter out toxic materials or uptake necessary nutrients. Meanwhile, malfunctioning proteins are responsible for a slew of disorders, including Alzheimer’s, type II diabetes, and Parkinson’s. Professor Mansbach want to understand and design small molecules and peptides for therapeutic applications such as finding new analgesics for treatment of chronic pain disorders, or correcting dysregulation of proteins that lead to Alzheimer’s. 

Potential Projects:

  • Drug Design for Antibiotics. Exploring the use of a fragment-based approach for novel antibiotic hybrid design through generative deep learning, in which a library of fragments relevant to antibiotic applications will be used as a basis for a generative model with a particular emphasis on interpretability as well as candidate generation. 
  • Antimicrobial Peptide (AMP) Design. Designing a deep learning model informed by multiscale molecular dynamics, wherein generative learning is used to iteratively create potential AMP candidates that are assessed on multiple scales using molecular dynamics.
  • Theory of disulfide bonds for toxin-based therapeutics. Using polymer theory or molecular dynamics, exploring ways to bring together constrained polymer theories with bond-breaking force field models to map out the free energy landscapes of disulfide-rich toxins for treatment of pain.

Professor Mansbach is also happy to work with students on their own ideas—as long as they fall within the broad scope of my work—and/or to tailor projects to suit specific strengths and interests.

This lab would like to cultivate an inclusive, diverse and collaborative lab environment. Members of traditionally underrepresented groups in STEM are strongly encouraged to apply.

 

Please contact ramansbach@gmail.com to apply!

 

Note for students unfamiliar with the Canadian graduate school system: generally, you need a MSc to advance to the PhD, although fast-tracking is possible if we can make a strong case for it. Professor Mansbach is happy to take someone for a MSc and  commit to sponsoring them on through the PhD; Professor Mansbach also happy to take students who solely want a MSc.

2020 Argonne Training Program on Extreme-Scale Computing (ATPESC)

By | Feature, SC2 jobs

2020 Argonne Training Program on Extreme-Scale Computing (ATPESC)

Application deadline: March 2, 2020.

There are no fees to participate in ATPESC. Domestic airfare, meals, and lodging are also provided.

Apply for an opportunity to learn the tools and techniques needed to carry out scientific computing research on the world’s most powerful supercomputers. ATPESC participants will be granted access to DOE’s leadership-class systems at the ALCF, OLCF, and NERSC. This year’s program will take place July 26–August 7, 2020.

PROGRAM CURRICULUM

Renowned scientists and leading HPC experts will serve as lecturers and guide the hands-on sessions. The core curriculum will cover:

  • Hardware architectures
  • Programming models and languages
  • Data-intensive computing and I/O
  • Visualization and data analysis
  • Numerical algorithms and software for extreme-scale science
  • Performance tools and debuggers
  • Software productivity
  • Machine learning and deep learning for science

ELIGIBILITY AND APPLICATION

Doctoral students, postdocs, and computational scientists interested in attending ATPESC can review eligibility and application details on the website.

Senior Scientist – Artificial Intelligence for R&D position available with the BASF Corporation

By | SC2 jobs

Senior Scientist – Artificial Intelligence for R&D with BASF

Location: Wyandotte, MI (preferred) or Tarrytown, NY

BASF is seeking a professional like you to join the Data Science community and shape the future of digitalization in Research and Development.  An Artificial Intelligence System (AI) observes its environment and takes actions that maximize its chance of success at a given goal. As AI expert, you will create such systems that learn and decide for multiple application areas in materials and systems research as well as process and quality control.

BASF will look to you to have demonstrated that you can build AI systems based on machine learning technology by integrating advanced algorithms with interfaces for sensors and actors.  In contrast to an isolated developer, you appreciate and understand experts from all areas of Data Science, including Automation & Information Technology, Data Analytics, and Data Management.  This is an excellent opportunity for you to demonstrate your experience in multiple projects using different IT environments (e.g. Lab Automation systems like LabView, Big Data systems like Hadoop; Machine Learning frameworks like scikit-learn; and programming languages like R or Python), your thorough understanding of data driven workflows, and your knowledge of statistical methods and their industrial application.  You will also share your agility, creativity, and entrepreneurial thinking with the team while feeling comfortable in a diverse, interdisciplinary, and challenging environment.  Your superior consultancy mindset with a high degree of flexibility and an ability to learn and adapt to new applications quickly will also be key to your success in this role.

Qualifications

  • BASF recognizes institutions of Higher Education which are accredited by the Council for Higher Education Accreditation or equivalent
  •  Leveraging your PhD in science or engineering with a focus on quantitative analytics (or equivalent qualification) and your experience in the field of Machine Learning and Artificial Intelligence – so much so that you are recognized as an expert, you will evaluate new approaches and explore new applications for AI.
  • Your experience in the Chemical (or related) industry and your excellent project management and collaboration skills will be essential as you initiate, execute, and lead AI projects in collaboration with research and business units in diverse high performing teams.
  • Demonstrating your international and industrial working experience, including your proven track record in working within multinational teams, filling the innovation pipeline, and executing projects with high business impact, you will define and develop novel AI solutions and liaise with academic experts and commercial providers.
  • Your excellent communication and interpersonal skills, along with your proven track record of relevant publications in peer-reviewed journals, will serve you well as you communicate and disseminate AI to a broad community of scientists and managers.

Visit the job positing for more information or to apply for the position.