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One (1) PROJECT TECHNICAL SPECIALIST I

 

 

Project title: MACHINE LEARNING OF PHYSICS-BASED EARTHQUAKE-INDUCED LANDSLIDE PARAMETERS AND FOR EFFICIENT PREDICTION AND WARNING IN THE PHILIPPINES (ML-PREP Project)

 

Employment status: Contract of Service Staff (COSS)

 

Contract Duration:Until 1st Semester of 2027, subject to Performance Evaluation every 6 months

 

Monthly Salary:Php52,272.00 /month

 

Educational Background

- Bachelor’s degree in Geotechnical Engineering, Civil Engineering, Geological Engineering, or a closely related field

Preferred: Master’s degree in Geotechnical or Civil Engineering with a specialization in soil mechanics or slope stability.

 

Duties and Responsibilities

- Conduct geotechnical analysis for earthquake-induced landslide (EIL) hazard modeling, including slope stability and soil mechanics studies

- Perform field investigations, including soil sampling, borehole logging, and geophysical surveys

- Analyze geotechnical properties such as cohesion, friction angle, unit weight, and soil saturation for hazard modeling

- Contribute to the preparation of Soil-Morphology Maps by integrating geotechnical data with GIS-based models

- Support deterministic modeling, including Newmark’s method, to calculate critical acceleration and factor of safety

- Develop and optimize geotechnical workflows and parameters for accurate hazard mapping

- Participate in preparing technical reports, hazard maps, and presentations for stakeholders, including LGUs and DRRM planners

- Assist in capacity-building activities, including workshops and training on geotechnical and seismic hazard assessment methods

- Maintain field and laboratory equipment, ensuring proper usage during geotechnical surveys

- Oversee and explore integration of research results with PHIVOLCS systems and workflows

- Must be willing to relocate at PHIVOLCS, Quezon City, Philippines

Experience/Training/Competencies:

Preferably a licensed professional with at least 1-2 years of relevant expertise in engineering geology, or civil or geotechnical engineering

Hands-on experience in slope stability analysis, soil testing, or seismic hazard assessments is an advantage.

Proficiency in geotechnical software (e.g., GeoStudio, Plaxis, Slide) for slope stability and soil analysis

- Familiarity with deterministic models, such as Newmark’s sliding block analysis

Experience with GIS tools for integrating geotechnical data into spatial models

Knowledge of geophysical survey techniques and equipment, such as seismic refraction and resistivity testing

- Basic programming skills (e.g., Python, R) for integrating geotechnical data into ML workflows.

 

To apply, go to the following link: https://push.carsu.edu.ph/dashboard/application_form/2025465 and click Apply Now

 


One (1) PROJECT TECHNICAL ASSISTANT IV

 

Project title: MACHINE LEARNING OF PHYSICS-BASED EARTHQUAKE-INDUCED LANDSLIDE PARAMETERS AND FOR EFFICIENT PREDICTION AND WARNING IN THE PHILIPPINES (ML-PREP Project)

 

Employment status: Contract of Service Staff (COSS)

 

Contract Duration:Until 1st Semester of 2027, subject to Performance Evaluation every 6 months

 

Monthly Salary:Php41,305.00/month

 

Educational Background

- Bachelor’s degree in Seismology, Geophysics, Geology, or a related field.

Preferred: Master’s degree in Seismology, Geophysics, or Earthquake Engineering with a focus on seismic hazard analysis.

 

Duties and Responsibilities

Conduct seismic hazard analysis, including the evaluation of ground shaking (GS), Peak Ground Acceleration (PGA), and Earthquake Intensity Scale (PEIS) parameters

- Collaborate with GIS specialists to develop regional seismic hazard maps for earthquake-induced landslide (EIL) assessments

- Analyze seismic wave propagation, topographic amplification, and site response using deterministic models such as the Spectral Element Method (SEM) and Newmark’s sliding block analysis

- Process and interpret seismic data from fieldwork and external datasets, ensuring accuracy for hazard modeling

- Integrate seismic data into Physics-Enhanced Machine Learning (PEML) workflows to improve predictive models for EIL hazards

- Conduct field surveys to collect data on seismic activities and their effects on local geomorphology and geotechnical conditions

- Work with remote sensing and geotechnical teams to assess earthquake-triggered landslides and validate hazard maps

- Participate in capacity-building activities, including training sessions and workshops for local government units (LGUs) and stakeholders

- Prepare technical reports, hazard models, and contributions to academic publications

- Oversee and explore integration of research results with PHIVOLCS systems and workflows

- Must be willing to relocate at PHIVOLCS, Quezon City, Philippines

 

Experience/Training/Competencies:

At least 1-2 years of experience in seismic hazard analysis, earthquake modeling, or related research fields.

Familiarity with seismic data processing software (e.g., SEISAN, SPECFEM, or REDAS).

Proficiency in seismic modeling techniques and tools such as SEM-Newmark displacement method

Experience with deterministic models for ground motion prediction and landslide assessment.

Knowledge of seismic data collection, interpretation, and validation.

Familiarity with GIS tools and geospatial data integration for seismic hazard mapping.

Basic programming skills in Python, MATLAB, or R for seismic data analysis and modeling.

Strong analytical and problem-solving skills for interpreting complex seismic data.

Effective communication skills for presenting technical findings to diverse audiences.

Ability to work collaboratively in interdisciplinary teams.

Willingness and physical fitness to conduct fieldwork in remote locations.

 

To apply, go to the following link: https://push.carsu.edu.ph/dashboard/application_form/2025481 and click Apply Now

 


 

One (1) PROJECT TECHNICAL ASSISTANT IV

 

 

Project title: MACHINE LEARNING OF PHYSICS-BASED EARTHQUAKE-INDUCED LANDSLIDE PARAMETERS AND FOR EFFICIENT PREDICTION AND WARNING IN THE PHILIPPINES (ML-PREP Project)

 

Employment status: Contract of Service Staff (COSS)

 

Contract Duration:Until 1st Semester of 2027, subject to Performance Evaluation every 6 months

 

Monthly Salary:Php41,305.00 /month

 

Educational Background

Bachelor’s degree in geology, computer science, Geoinformatics, Geospatial Science, Earth Science, or related fields.

Preferred: Master’s degree in geology, computer science, Disaster Risk Management, or related fields.

 

Duties and Responsibilities

- Develop and manage Geographic Information System GIS based workflows for creating and analyzing ground shaking GS and earthquake induced landslide EIL hazard maps.

- Process and analyze spatial data, including digital elevation models DEMs, IfSAR, and geotechnical datasets, for hazard modeling.Create detailed geospatial visualizations and thematic maps for hazard assessment and stakeholder communication.

- Integrate remote sensing outputs, field data, and deterministic models e.g., Newmark analysis into GIS platforms for hazard mapping.Conduct spatial analysis to identify areas prone to seismic and landslide hazards, optimizing parameters for high resolution mapping.

- Maintain and manage geospatial databases, ensuring data quality, accuracy, and accessibility for project use.

- Support field data collection by designing and updating GIS field mapping tools and systems.

- Assist in report preparation, training sessions, and workshops for stakeholders, including LGUs and disaster risk reduction teams

- Oversee and explore integration of research results with PHIVOLCS systems and workflows

- Must be willing to relocate at PHIVOLCS, Quezon City, Philippines.

 

Experience/Training/Competencies:

At least 1–2 years of experience in GIS-based spatial analysis and modeling.

Hands-on experience in disaster risk assessment, hazard mapping, or similar projects is an advantage

Proficiency in GIS software (e.g., ArcGIS, QGIS, PostGIS) for data manipulation and spatial analysis.

Familiarity with geospatial programming languages (e.g., Python, R) for automating workflows and data processing.

Experience working with satellite imagery and remote sensing data for terrain analysis and hazard modeling.

Knowledge of DEM processing, terrain modeling, and geospatial data visualization techniques.

Understanding of geodatabase management and spatial data standards.

Familiarity with integrating GIS outputs into machine learning workflows is a plus.

Strong analytical and problem-solving skills for interpreting spatial data.

Effective communication skills to convey technical results to multidisciplinary teams and stakeholders.

Ability to manage multiple tasks and meet project deadlines.

Team-oriented with good collaboration skills for interdisciplinary projects.

 

To apply, go to the following link: https://push.carsu.edu.ph/dashboard/application_form/2025480 and click Apply Now

 

For the document screening, Kindly create your own Google Drive folder with the following naming convention and share the access with anyone with the link:
Note: Please follow the naming convention below
Folder name: (Family Name)_(Hiring Office)-(the position your applying)
File name: (Family Name)_(Hiring Office)-(the position your applying)_(file to upload)

Application/Cover Letter addressed to the CSU President Dr. Rolyn C. Daguil

One (1) copy of duly accomplished and Notarized Personal Data Sheet (Indicating education, experience and no. of hours of training/seminars)

Authenticated Copy Transcript of Records

Certificates of Relevant Trainings and Seminars attended

Certificate of Employment

Work Experience Sheet

SSS/PHILHEALTH/PAG-IBIG AND TAX IDENTIFICATION NUMBER

 

As an advocate of the Equal Employment Opportunity Principle (EEOP), the DOST-PHIVOLCS encourages and welcomes all applicants regardless of age, religion, political affiliation including persons with disability, members of indigenous communities, and those from any sexual orientation and gender identities.

 

APPLICATIONS WITH INCOMPLETE DOCUMENTS SHALL NOT BE ENTERTAINED. Only qualified applicants will be contacted.

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