ATTN: Undergraduate Engineering, Chemistry, and Oceanography students

A lab-based course will be offered this Fall 2019 quarter on the SIO campus! Students enrolled in this course will have the opportunity to work as a team to develop instruments with oceanography applications. Specifically, students will have the experience of engaging in the overhaul and calibration of an autonomous sensor package that is used to measure and report real-time data (pH, oxygen, temperature, salinity, pressure) from the Agua Hedionda Lagoon in Carlsbad.  

Students will be split into teams of 2-3, each with a specific area of focus (e.g. CAD, microcontroller, chemical method) and provided the choice to either work in their area of expertise or collaborate with others in an area of improvement.

SIO 179 – Marine Instrumental Methods

Fall qtr. 2019

Instructor:       Todd Martz, MESOM 337, x47466, trmartz@ucsd.edu

Location:         Scripps Makerspace

Time:               Mon, 11-12 (Lecture); Tue/Thurs 9am – 1pm (Lab)

Theme

Apply modern and classic techniques for analysis of seawater, introducing concepts of signal transduction, calibration, and measurement quality control.  Emphasis will be placed on computer automation to perform basic functions including instrument control, data storage, and on-the-fly calculations.  Students will apply techniques from several branches of engineering to the marine sciences.

Requirements

This is a hands-on laboratory course.  Students will complete a single term or several multi-week projects, working in groups of 2-3, and prepare one PowerPoint report per group per exercise.  Class meets once per week for up to 2 hours to cover theoretical overview and open discussion of the experiment or data analysis.  Homework will be in the form of laboratory preparation and completion of reports.

Laboratory time will be scheduled by the instructor based on availability of equipment and individual teams’ schedules and is expected to require ~6-8 hours per week.  Grades will be based on participation in lab, quality of the reports. Grading considerations will include comprehension of the material, presentation of data (i.e. quality of graphs, figures, and tables), data interpretation, report organization & overall clarity.  All lab reports undergo a single revision cycle and the grade is based on the revised report.

Prerequisite Knowledge

No prerequisite courses are required, but the advanced nature of projects is intended for those with some background knowledge in at least one area of engineering, physics, or chemistry.  Advanced concepts related to marine chemistry and engineering will be introduced and reviewed as needed. 

Course Materials

·         Computers and a variety of development tools will be available in the makerspace.

·         A variety of research quality instruments and sensors will be available through the instructor’s laboratory.

·         Any additional materials will be discussed during the first class period.

NANO 102 – Foundations in Nanoengineering: Chemical Principles

Professor Andrea Tao is offering a four-unit course on chemical principles involved in synthesis, assembly, and performance of nanostructured materials and devices. Chemical interactions, classical and statistical thermodynamics of small systems, diffusion, carbon–based nanomaterials, supramolecular chemistry, liquid crystals, colloid and polymer chemistry, lipid vesicles, surface modification, surface functionalization, catalysis. 

Prerequisites for the course include: Chem. 6C, Math. 20D, PHYS 2D, NANO 101, NANO 106

Students can petition to take the course concurrently with PHYS 2D. Students with majors in the Chemistry and Biochemistry Department can use this class to fulfill an open elective by submitting a pre-approval petition. See petition details here.

Center for Statistics and Machine Learning – Job Posting

JOB DESCRIPTION:  DATA SCIENTIST – SCHMIDT DATA X PROJECT, PRINCETON UNIVERSITY

Do you want to apply your data science and computational skills to exciting new research problems? Do you have a background in research but love to write code and analyze data? If so, then we have an exciting opportunity for you.

Princeton University is building a community of data scientists to work in partnership with its world-renowned faculty and students to help solve data-driven research problems. You will work with faculty in a collaborative, multidisciplinary environment and actively contribute your skills to advance scientific discovery. You will have access to Princeton’s first-class resources, the opportunity to co-author academic publications, to offer short courses and workshops on data science, and to collaborate with, and learn from, the larger computational data science community.

Three research areas are of particular interest. Catalysis: led by the Department of Chemistry; Biomedical Data Science: led by the Department of Computer Science; Technology Policy: led by the Center for Information Technology Policy. Prior experience in one of the above areas is an asset but is not required. You will be mentored in the relevant research area. If you have a strong background in scientific programming, academic research, and are eager to contribute to groundbreaking research, you have the right skill set. These are 3-year appointments offering a very competitive salary and excellent opportunities for growth and career development. The positions are part of the Schmidt DataX project, an initiative made possible by a major gift from Schmidt Futures.

Responsibilities:

  • Integrate with interdisciplinary research teams and creatively develop/apply modern data science, statistics, and machine learning techniques to advance research.
  • Coding/algorithmic prototyping of relevant analysis methods, including setting clear goals, measuring progress, and the creation of appropriate documentation.
  • Collaborate with, educate, convene, and support a broad community of researchers on campus in how to best leverage data science in their teaching and research. This may include contributing to mini-courses and workshops on data science.
  • Communicate results and impact to all stakeholders. This may include presenting research at academic conferences and workshops.

Required Qualifications:

  • PhD required in computer science or related discipline; or equivalent combination of educational training, relevant experience, and accomplishments.
  • Strong coding/algorithm prototyping skills, and ability to explain and document work.
  • Proficiency in one or more of the following: Python, C, C++, SQL.
  • Experience working in data analysis/statistics/machine learning/scientific computing to address basic research questions; or commensurate achievements.

Additional Desired Qualifications:

  • Strong problem-solving skills; a passion for answering hard questions with data.
  • The ability to communicate complex ideas to relevant stakeholders.
  • Experience in a collaborative, multi-disciplinary research environment.
  • Eagerness to collaborate with both technical and non-technical colleagues.
  • Experience in database design and building data-driven web applications.

Princeton provides an exceptional work environment that includes a comprehensive set of programs and benefits for you, your spouse or domestic partner, and your family including: competitive health, dental, vision and life insurance; generous vacation and sick leave packages; retirement planning with a generous company match; competitive parental leave; Backup Care Advantage for child or elder care.

Access application at https://www.princeton.edu/acad-positions/position/13062. Please include a cover letter (preferred) or writing sample, curriculum vitae, and names and contact information of three references. References will only be contacted if you are a finalist.

Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. This position is subject to the University’s background check policy.



Questions?  Feel free to contact our Project Manager, Ellen DiPippo if you have any questions
                     about the position or process. 

Ready to Apply:  Please use A-Hire, Princeton’s internal job posting system to apply:  https://www.princeton.edu/acad-positions/position/13062

Physical Sciences Drop-In Advising

Colorado School of Mines – Open Position

Marketing Internship

PSC Biotech Corporation is looking to hire two marketing interns. See message below for details!

We’re looking for two students who are passionate about marketing and are interested in the life science and/or software industries. We’re really looking for students who could truly be involved with our marketing efforts while balancing their education. We’re opened to any student pursuing a marketing or life science degree.

All the best,

Olivia Lepore

Marketing Specialist

PSC Biotech Corporation

700 Corporate Center Drive Pomona, CA 91768

Office (909) 784-3350 | Mobile (617) 803-9193

UCLA – Temporary Lecturer Position

The UCLA Department of Chemistry & Biochemistry seeks applications for temporary lecturer positions to teach undergraduate Organic Chemistry courses during the Fall 2019 and Winter 2020 Quarters. 

Interested candidates may apply through the links below:

https://recruit.apo.ucla.edu/JPF04649

Sincerely,

Anastassia Alexandrova, Ph.D.

Vice Chair of Undergraduate Education

Associate Professor

UCLA Department of Chemistry & Biochemistry