Jobs/Internships

Description:

We have a postdoc position in an exciting multidisciplinary project to develop an innovative smart shoe system for ankle injury prevention, which is funded by the National Institute of Arthritis and Musculoskeletal and Skin Disease (NIAMS). The smart shoe system integrates machine learning-based wearable sensor data processing, a soft robotic ankle device with stiffness adjustment capability, sophisticated biomechanical models of foot-ankle mechanics, advanced injury risk prediction and control algorithms, and an intuitive user interface with real-time and summative injury risk metrics. The postdoc will work with Drs. Hyunglae Lee, Pavan Turaga, Sze Zheng Yong, and Matthew Buman and multiple graduate students with diverse backgrounds in biomechanics, soft robotics, controls, machine learning, and behavioral science. The position is available to start immediately.

Responsibilities:

• Development of machine learning algorithms (especially, deep learning) for robust sensor data processing and activity recognition
• Design and implementation of prediction and control algorithms to provide active assist-as-needed ankle support
• Integration of the machine learning and control algorithms into the soft robotic ankle device
• Device testing, validation, and troubleshooting
• Subject recruitment, design of experiment, biomechanics data collection, processing, analysis, and interpretation
• Participation in user studies for the design of a mobile app to support the smart shoe system
• Mentoring graduate students for seamless integration of device development and machine learning and control algorithms
• Presentation and publication of results in robotics, controls, and/or ML conferences and journals

Eligibility and Qualifications

• Must have a PhD in Mechanical Engineering, Robotics, Computer Science, or related field
• Must have research achievements and interest in one or more of the above-mentioned topics (i.e., soft robotics, controls, and machine learning)
• Advanced programming skills (e.g., MATLAB/Simulink, Python, C/C++, ROS)
• Strong hands-on debugging and troubleshooting skills with sensors and robotic devices
• Candidates who have experience with motion analysis equipment (e.g., motion capture system, force plate, IMUs, insole sensors) and system identification for physiological systems are particularly welcomed

Application deadline

• On a rolling basis

To be considered for this position, please email Dr. Hyunglae Lee (email: hyunglae.lee@asu.edu) with 1) CV/Resume, 2) transcripts, 3) a single-page statement of purpose, and 4) a list of two or three references

Two Postdoctoral Fellow (or Research Engineer/Scientist) positions in the Woodruff School of Mechanical
Engineering at Georgia Tech
Ideal candidates should have strong background and publication record in one or more of the following:

• Structural dynamics/vibration, elastic/acoustic waves, metamaterials/phononics
• Ultrasonics, piezoelectric transducers, electromechanical systems, multiphysics problems (fluid-structure
  interaction, acoustic-structure interaction, etc.)
• Dynamical systems theory/applications, inverse problems, machine learning, neural networks
  The Smart Structures & Dynamical Systems Lab (SSDSL) at Georgia Tech offers a diverse and collaborative
  environment with excellent professional growth opportunities. SSDSL alumni include faculty at top research
  universities, engineers in government labs and corporate research, among others.
  Postdoctoral Fellows (or Research Engineer/Scientist for senior applicants) will have exciting opportunities to
  engage in highly interdisciplinary projects, collaborate with/supervise graduate students and visiting scholars,
  and expand their knowledge and skills in a lab that aims to strike a balance between theory and experiment.
  Interested candidates should email their CVs/questions to Prof. Alper Erturk (alper.erturk@me.gatech.edu).

The Department of Mechanical Engineering at the University of Maine invites applications for a
full-time, tenure-track Assistant Professor position with an anticipated start date of January
2023 or earlier.

Required Qualifications:
● A Ph.D. in aerospace engineering, mechanical engineering, ocean engineering, or a
closely related field by date of hire.
● A well-documented record of high-quality research in fluid mechanics, specifically in CFD
and numerical modeling of internal and/or external flow fields.
● Evidence of a strong potential for obtaining extramural funding and supporting graduate
students.
● Evidence of a strong potential for teaching excellence, and capability to develop and
teach fluid mechanics and CFD courses at the undergraduate and graduate levels.
● Excellent communication skills and teamwork ability.
● A commitment to diversity, equity, and inclusion in education, research, and service.
Preferred Qualifications:
● Potential for collaboration in one or more areas including aerospace, mechanical, ocean,
energy and biomedical engineering.
● Experience in experimental fluid mechanics is desirable as a complement to numerical
modelling expertise.
● Industrial experience in fluid mechanics is desirable.

This is a 50% teaching, 50% research position in mechanical engineering and requires active
engagement in service to the University, the State, and the profession. The successful candidate
will be expected to lead an externally-funded research program, develop and teach
undergraduate and graduate courses, advise and mentor students, publish and present
scholarly works, participate in service activities, and demonstrate commitment to diversity,
equity and inclusion. We highly encourage and welcome applications from all genders and
members of historically underrepresented groups.

For more information and to apply for this position, go to https://umaine.hiretouch.com/jobdetails?jobid=76993

Applicants should submit

(1) cover letter which describes your experience, interests, and
suitability for the position

(2) resume/curriculum vitae

(3) teaching philosophy

(4) research statement

(5) contact information for three professional references, including postal and
email addresses and phone numbers.

Review of applications will begin on August 1, 2022 and
will continue until the position is filled.

The University of Maine is an EEO/AA employer, and does not discriminate on the grounds of
race, color, religion, sex, sexual orientation, transgender status, gender expression, national
origin, citizenship status, age, disability, genetic information or veteran’s status in
employment, education, and all other programs and activities. The following person has been
designated to handle inquiries regarding non-discrimination policies: Amie Parker, Interim
Director of Equal Opportunity, 101 North Stevens Hall, University of Maine, Orono, ME
04469-5754, 207.581.1226, TTY 711 (Maine Relay System).

The newly established Mathematical Institute for Machine Learning and Data Science (MIDS) at KU Eichstätt-Ingolstadt (KUEI) invites applications for a full-time position (100%) at the next possible date for a Akademischer Rat auf Zeit (m/f/d) with an initial contract duration of 3 years with a possible extension for another 2 years. The place of work is Ingolstadt, Germany. Provided that the requirements are met, remuneration will be according to A13 or E13 TV-L pay grade.

The successful candidate pursues independent research at the interface of data assimilation, modeling, machine learning, uncertainty quantification and applications in geosciences. Subfields of particular interest include data-driven algorithms, optimization and applications in weather forecasting. The possibility of habilitation is given and is expressly desired.

Your tasks
· Independent research and publications
· Light teaching duties within the teaching portfolio of the MIDS (equivalent to 5 hours per week during the teaching period)
· Acquisition of third-party funding
· Participation in the research activities of the group
· Contribution to larger structured funding proposals

Your profile
· Excellent PhD degree in physics, atmospheric sciences or applied mathematics
· Ability to work in a team
· Ability to structure and pursue a successful research agenda
· Flexibility and willingness to travel
· German language skills are not required, but candidates are encouraged to develop those during their employment at the KUEI

Our offer
· Participation in the development of the newly founded Mathematical Institute for Machine Learning and Data Science (MIDS)
· Team-oriented and well-equipped work environment in central Ingolstadt
· Possibility to pursue own research
· Opportunity and support for career development

Your application
Please send your application with the usual supporting documents by e-mail to Prof. Dr. Tijana Janjic (tijana.janjic@ku.de) by September 2nd, 2022 (please combine all documents in one PDF file). Your documents should include cover letter, curriculum vitae, copies of transcripts and degree certificates and at least one letter of recommendation. Applicants’ documents will be deleted after completion of the recruitment process in compliance with data protection regulations.

The newly established Department of Design at Indian Institute of
Technology in Kanpur, India is very actively looking for individuals with
excellent academic and research record for full-time positions of
Mechanical Engineering Professor, Associate Professor, and Assistant
Professor.

Successful candidates will teach and conduct research in diverse areas of
Design, including those related to mechanical engineering. The attached
document provides details about our hiring needs.

If interest, contact Nachiketa Tiwari at ntiwari@iitk.ac.in.

 Southern Nuclear Company is looking for a couple of early-career PRA engineers/or SR PRA engineers to support us.  Southern Nuclear is a great place to work with very supportive of innovative research, constantly improving and growing (Vogtle Unit 3 is about to come online with unit 4 to follow shortly after), and they are on the way to fully implementing High enrichment fuel as soon as they have test assembly out for testing. 

If interested, contact Faramarz Pournia at fpournia@southernco.com

Reliability, Availability, and Maintainability (RAM) Lead

General Responsibilities
 Coordinate with the Operational Test Director and Lead Evaluator on Reliability, Availability, and
Maintainability (RAM)
 Performs analysis of documented user requirements and directs or assists in the design of test plans in
support of user requirements for moderately complex to complex RAM utilization to supplement OT&E
activities
 Participates in all phases of risk management assessment and software/hardware development
 Responsible for ensuring that the RAM test design and documentation support all applicable clients, agency
or industry standards timelines and budgets
 Coordinates and synchronizes evaluation activities and events with the Government T&E Manager and
other program and external stakeholders on RAM activity
 Responsible for ensuring that RAM conclusions and recommendations are fully supported by test results
 Coordinates OT&E evaluation status, strategies, plans, briefs and reports with other team members
 Presents briefs to DHS DOT&E
Skills Required
 Selected candidate must be trained/certified to the DHS T&E Certification Level II equivalency and
certified or willing to completed the DHS Operational Test Director (OTD) Training Course
 Must possess at least 7 years of experience in the RAM test and evaluation field and have experience
supporting DHS or equivalent Operational Test Agent services
 Selected candidate must be able to respond quickly to requirements and tasks with stringent deadlines in a demanding homeland security environment; possess strong critical thinking abilities and judgment skills; and be able to interact with various levels of people within and outside of a Government organization.
 Selected candidate must have knowledge and/or experience with DHS Acquisition Directives and
Acquisition Lifecycle Framework (AD102/ALF); knowledge, understanding and/or experience with the
DHS (or DoD equivalent) Test and Evaluation (T&E) policies, procedures and best practices for conducting,
monitoring and reviewing operational test and evaluation.
 Selected candidate must be able to support and perform assessments of T&E artifacts, such as the T&E
Master Plan (TEMP), Developmental Test and Evaluation Plans, Operational Test and Evaluation Plans,
Operational Requirements Documents, Mission Needs Statements with regard to RAM Testing, data
collection, and evaluation.
 Demonstrates written and oral communication skills – provides technical guidance to the project team in performance of the work, and reviews the quality of all work products.

 If interested, contact Tom Roltsch at roltsch@umd.edu or 703-915-1807.

There is an opportunity for one potential PhD student to join FDA for a summer internship or a postdoctoral program to work on battery life time and longevity modeling and test methods for implants.

Key Roles
• Develop, improve, and validate battery models for better prediction of lithium-ion battery
performance and lifetime
• Formulate experiments to acquire data to train, validate and test battery models and aging
models
• Design and investigate test procedures as well as trade-off analysis to capture and improve
model parameters under all working conditions
• Explore and expand modeling capability to include various features such as balancing, SEI
layer growth, lithium plating, thermal runaway, etc.
• Work with cross-functional teams to develop and implement validated battery models for
different uses
• Generate simulation summary data/charts/reports
• Perform data analysis of cell/module/pack characterization tests
• Develop machine learning models for data analysis, optimization and prediction is plus

Basic Qualifications
• Ph.D. in engineering with battery modeling experience
• Fundamental knowledge of lithium-ion cell electrochemical model, electrical circuit model,
thermal model, and aging model
• Experienced in multiphysics-based models for electrochemical/electrical/thermal systems, as
well as aging mechanisms
• Proficiency in using MATLAB/Simulink, and other multiphysics software tools such as GT-
Autolion, COMSOL, BDS-STARCCM+, etc for battery simulation
• Exposure in using machine learning models for battery health prediction and optimization
• Familiar with battery testing protocols and efficient in writing codes to process and analyze
large data sets

If you are interested, please email your CV to this email address: hamed.ghods@fda.hhs.gov

Stanford’s Department of Mechanical Engineering at Stanford invites applications for a teaching professor, at all levels of seniority, with specialization in topics related to design and manufacturing:

https://facultypositions.stanford.edu/en-us/job/493407/professor-teaching-all-ranks-in-mechanical-engineering

The ideal applicant has a strong commitment to teaching, knowledge of pedagogical research, a track record of effective instruction, experience developing new courses, and a national reputation in Mechanical Engineering education, or, for junior applicants, potential for the same.

The successful candidate will have the opportunity to shape our department’s future in design and making education. The candidate will teach classes, typically two per academic quarter, develop undergraduate curriculum, and provide leadership in the broader Mechanical Engineering educational community.